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17,200
haifengl/smile
math/src/main/java/smile/math/matrix/QR.java
QR.getR
public DenseMatrix getR() { int n = qr.ncols(); DenseMatrix R = Matrix.zeros(n, n); for (int i = 0; i < n; i++) { R.set(i, i, tau[i]); for (int j = i+1; j < n; j++) { R.set(i, j, qr.get(i, j)); } } return R; }
java
public DenseMatrix getR() { int n = qr.ncols(); DenseMatrix R = Matrix.zeros(n, n); for (int i = 0; i < n; i++) { R.set(i, i, tau[i]); for (int j = i+1; j < n; j++) { R.set(i, j, qr.get(i, j)); } } return R; }
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Returns the upper triangular factor.
[ "Returns", "the", "upper", "triangular", "factor", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/math/src/main/java/smile/math/matrix/QR.java#L88-L98
17,201
haifengl/smile
math/src/main/java/smile/math/matrix/QR.java
QR.getQ
public DenseMatrix getQ() { int m = qr.nrows(); int n = qr.ncols(); DenseMatrix Q = Matrix.zeros(m, n); for (int k = n - 1; k >= 0; k--) { Q.set(k, k, 1.0); for (int j = k; j < n; j++) { if (qr.get(k, k) != 0) { double s = 0.0; ...
java
public DenseMatrix getQ() { int m = qr.nrows(); int n = qr.ncols(); DenseMatrix Q = Matrix.zeros(m, n); for (int k = n - 1; k >= 0; k--) { Q.set(k, k, 1.0); for (int j = k; j < n; j++) { if (qr.get(k, k) != 0) { double s = 0.0; ...
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Returns the orthogonal factor.
[ "Returns", "the", "orthogonal", "factor", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/math/src/main/java/smile/math/matrix/QR.java#L103-L123
17,202
haifengl/smile
data/src/main/java/smile/data/parser/SparseDatasetParser.java
SparseDatasetParser.parse
public SparseDataset parse(String name, InputStream stream) throws IOException, ParseException { BufferedReader reader = new BufferedReader(new InputStreamReader(stream)); try { // process header int nrow = 1; String line = reader.readLine(); for (; nrow <...
java
public SparseDataset parse(String name, InputStream stream) throws IOException, ParseException { BufferedReader reader = new BufferedReader(new InputStreamReader(stream)); try { // process header int nrow = 1; String line = reader.readLine(); for (; nrow <...
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Parse a sparse dataset from an input stream. @param name the name of dataset. @param stream the input stream of data. @throws java.io.IOException
[ "Parse", "a", "sparse", "dataset", "from", "an", "input", "stream", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/data/src/main/java/smile/data/parser/SparseDatasetParser.java#L151-L189
17,203
haifengl/smile
math/src/main/java/smile/sort/PriorityQueue.java
PriorityQueue.swap
private void swap(int i, int j) { int t = pq[i]; pq[i] = pq[j]; pq[j] = t; qp[pq[i]] = i; qp[pq[j]] = j; }
java
private void swap(int i, int j) { int t = pq[i]; pq[i] = pq[j]; pq[j] = t; qp[pq[i]] = i; qp[pq[j]] = j; }
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Swap i and j items of pq and qp. @param i item index @param j item index
[ "Swap", "i", "and", "j", "items", "of", "pq", "and", "qp", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/math/src/main/java/smile/sort/PriorityQueue.java#L63-L69
17,204
haifengl/smile
math/src/main/java/smile/sort/PriorityQueue.java
PriorityQueue.swim
private void swim(int k) { while (k > 1 && less(k, (k + d - 2) / d)) { swap(k, (k + d - 2) / d); k = (k + d - 2) / d; } }
java
private void swim(int k) { while (k > 1 && less(k, (k + d - 2) / d)) { swap(k, (k + d - 2) / d); k = (k + d - 2) / d; } }
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fix up.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/math/src/main/java/smile/sort/PriorityQueue.java#L74-L79
17,205
haifengl/smile
math/src/main/java/smile/sort/PriorityQueue.java
PriorityQueue.sink
private void sink(int k, int N) { int j; while ((j = d * (k - 1) + 2) <= N) { for (int i = j + 1; i < j + d && i <= N; i++) { if (less(i, j)) { j = i; } } if (!(less(j, k))) { break; } ...
java
private void sink(int k, int N) { int j; while ((j = d * (k - 1) + 2) <= N) { for (int i = j + 1; i < j + d && i <= N; i++) { if (less(i, j)) { j = i; } } if (!(less(j, k))) { break; } ...
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fix down.
[ "fix", "down", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/math/src/main/java/smile/sort/PriorityQueue.java#L84-L98
17,206
haifengl/smile
math/src/main/java/smile/sort/PriorityQueue.java
PriorityQueue.insert
public void insert(int v) { pq[++n] = v; qp[v] = n; swim(n); }
java
public void insert(int v) { pq[++n] = v; qp[v] = n; swim(n); }
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Insert a new item into queue. @param v the index of item.
[ "Insert", "a", "new", "item", "into", "queue", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/math/src/main/java/smile/sort/PriorityQueue.java#L132-L136
17,207
haifengl/smile
math/src/main/java/smile/math/special/Erf.java
Erf.inverfc
public static double inverfc(double p) { double x, err, t, pp; if (p >= 2.0) { return -100.; } if (p <= 0.0) { return 100.; } pp = (p < 1.0) ? p : 2. - p; t = Math.sqrt(-2. * Math.log(pp / 2.)); x = -0.70711 * ((2.30753 + t * 0.2706...
java
public static double inverfc(double p) { double x, err, t, pp; if (p >= 2.0) { return -100.; } if (p <= 0.0) { return 100.; } pp = (p < 1.0) ? p : 2. - p; t = Math.sqrt(-2. * Math.log(pp / 2.)); x = -0.70711 * ((2.30753 + t * 0.2706...
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The inverse complementary error function.
[ "The", "inverse", "complementary", "error", "function", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/math/src/main/java/smile/math/special/Erf.java#L104-L120
17,208
haifengl/smile
math/src/main/java/smile/math/special/Gamma.java
Gamma.digamma
public static double digamma(double x) { final double C7[][] = { { 1.3524999667726346383e4, 4.5285601699547289655e4, 4.5135168469736662555e4, 1.8529011818582610168e4, 3.3291525149406935532e3, 2.4068032474357201831e2, 5.15778920001390847...
java
public static double digamma(double x) { final double C7[][] = { { 1.3524999667726346383e4, 4.5285601699547289655e4, 4.5135168469736662555e4, 1.8529011818582610168e4, 3.3291525149406935532e3, 2.4068032474357201831e2, 5.15778920001390847...
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The digamma function is defined as the logarithmic derivative of the gamma function.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/math/src/main/java/smile/math/special/Gamma.java#L265-L320
17,209
haifengl/smile
math/src/main/java/smile/math/special/Gamma.java
Gamma.inverseRegularizedIncompleteGamma
public static double inverseRegularizedIncompleteGamma(double a, double p) { if (a <= 0.0) { throw new IllegalArgumentException("a must be pos in invgammap"); } final double EPS = 1.0E-8; double x, err, t, u, pp; double lna1 = 0.0; double afac = 0.0; ...
java
public static double inverseRegularizedIncompleteGamma(double a, double p) { if (a <= 0.0) { throw new IllegalArgumentException("a must be pos in invgammap"); } final double EPS = 1.0E-8; double x, err, t, u, pp; double lna1 = 0.0; double afac = 0.0; ...
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The inverse of regularized incomplete gamma function.
[ "The", "inverse", "of", "regularized", "incomplete", "gamma", "function", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/math/src/main/java/smile/math/special/Gamma.java#L325-L383
17,210
haifengl/smile
core/src/main/java/smile/clustering/FastPair.java
FastPair.findNeighbor
private void findNeighbor(int p) { // if no neighbors available, set flag for UpdatePoint to find if (npoints == 1) { neighbor[p] = p; distance[p] = Float.MAX_VALUE; return; } // find first point unequal to p itself int first = 0; if (...
java
private void findNeighbor(int p) { // if no neighbors available, set flag for UpdatePoint to find if (npoints == 1) { neighbor[p] = p; distance[p] = Float.MAX_VALUE; return; } // find first point unequal to p itself int first = 0; if (...
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Find nearest neighbor of a given point.
[ "Find", "nearest", "neighbor", "of", "a", "given", "point", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/clustering/FastPair.java#L102-L130
17,211
haifengl/smile
core/src/main/java/smile/clustering/FastPair.java
FastPair.remove
public void remove(int p) { npoints--; int q = index[p]; index[points[q] = points[npoints]] = q; for (int i = 0; i < npoints; i++) { if (neighbor[points[i]] == p) { findNeighbor(points[i]); } } }
java
public void remove(int p) { npoints--; int q = index[p]; index[points[q] = points[npoints]] = q; for (int i = 0; i < npoints; i++) { if (neighbor[points[i]] == p) { findNeighbor(points[i]); } } }
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Remove a point and update neighbors of points for which it had been nearest
[ "Remove", "a", "point", "and", "update", "neighbors", "of", "points", "for", "which", "it", "had", "been", "nearest" ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/clustering/FastPair.java#L143-L153
17,212
haifengl/smile
core/src/main/java/smile/clustering/FastPair.java
FastPair.getNearestPair
public double getNearestPair(int[] pair) { if (npoints < 2) { throw new IllegalStateException("FastPair: not enough points to form pair"); } double d = distance[points[0]]; int r = 0; for (int i = 1; i < npoints; i++) { if (distance[points[i]] < d) { ...
java
public double getNearestPair(int[] pair) { if (npoints < 2) { throw new IllegalStateException("FastPair: not enough points to form pair"); } double d = distance[points[0]]; int r = 0; for (int i = 1; i < npoints; i++) { if (distance[points[i]] < d) { ...
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Find closest pair by scanning list of nearest neighbors
[ "Find", "closest", "pair", "by", "scanning", "list", "of", "nearest", "neighbors" ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/clustering/FastPair.java#L158-L182
17,213
haifengl/smile
core/src/main/java/smile/clustering/FastPair.java
FastPair.updatePoint
public void updatePoint(int p) { neighbor[p] = p; // flag for not yet found any distance[p] = Float.MAX_VALUE; for (int i = 0; i < npoints; i++) { int q = points[i]; if (q != p) { float d = linkage.d(p, q); if (d < distance[p]) { ...
java
public void updatePoint(int p) { neighbor[p] = p; // flag for not yet found any distance[p] = Float.MAX_VALUE; for (int i = 0; i < npoints; i++) { int q = points[i]; if (q != p) { float d = linkage.d(p, q); if (d < distance[p]) { ...
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All distances to point have changed, check if our structures are ok Note that although we completely recompute the neighbors of p, we don't explicitly call findNeighbor, since that would double the number of distance computations made by this routine. Also, like deletion, we don't change any other point's neighbor to p...
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/clustering/FastPair.java#L191-L211
17,214
haifengl/smile
core/src/main/java/smile/clustering/FastPair.java
FastPair.updateDistance
public void updateDistance(int p, int q) { float d = linkage.d(p, q); if (d < distance[p]) { distance[p] = q; neighbor[p] = q; } else if (neighbor[p] == q && d > distance[p]) { findNeighbor(p); } if (d < distance[q]) { distance[q]...
java
public void updateDistance(int p, int q) { float d = linkage.d(p, q); if (d < distance[p]) { distance[p] = q; neighbor[p] = q; } else if (neighbor[p] == q && d > distance[p]) { findNeighbor(p); } if (d < distance[q]) { distance[q]...
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Single distance has changed, check if our structures are ok.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/clustering/FastPair.java#L216-L232
17,215
haifengl/smile
core/src/main/java/smile/classification/LogisticRegression.java
LogisticRegression.softmax
private static void softmax(double[] prob) { double max = Double.NEGATIVE_INFINITY; for (int i = 0; i < prob.length; i++) { if (prob[i] > max) { max = prob[i]; } } double Z = 0.0; for (int i = 0; i < prob.length; i++) { double ...
java
private static void softmax(double[] prob) { double max = Double.NEGATIVE_INFINITY; for (int i = 0; i < prob.length; i++) { if (prob[i] > max) { max = prob[i]; } } double Z = 0.0; for (int i = 0; i < prob.length; i++) { double ...
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Calculate softmax function without overflow.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/classification/LogisticRegression.java#L932-L950
17,216
haifengl/smile
plot/src/main/java/smile/plot/Contour.java
Contour.isIntersect
private boolean isIntersect(double z0, double z1, double zc) { if ((z0 - zc) * (z1 - zc) < 0.0) { return true; } return false; }
java
private boolean isIntersect(double z0, double z1, double zc) { if ((z0 - zc) * (z1 - zc) < 0.0) { return true; } return false; }
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Returns true if zc is between z0 and z1.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/Contour.java#L807-L813
17,217
haifengl/smile
plot/src/main/java/smile/plot/Contour.java
Contour.segdir
private int segdir(double xend, double yend, int[] ij) { if (YMATCH(yend, y[ij[1]])) { if (ij[1] == 0) { return 0; } ij[1] -= 1; return 3; } if (XMATCH(xend, x[ij[0]])) { if (ij[0] == 0) { return 0; ...
java
private int segdir(double xend, double yend, int[] ij) { if (YMATCH(yend, y[ij[1]])) { if (ij[1] == 0) { return 0; } ij[1] -= 1; return 3; } if (XMATCH(xend, x[ij[0]])) { if (ij[0] == 0) { return 0; ...
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Determine the entry direction to the next cell and update the cell indices.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/Contour.java#L834-L868
17,218
haifengl/smile
core/src/main/java/smile/association/FPTree.java
FPTree.freq
private static int[] freq(int[][] itemsets) { int[] f = new int[Math.max(itemsets) + 1]; for (int[] itemset : itemsets) { for (int i : itemset) { f[i]++; } } return f; }
java
private static int[] freq(int[][] itemsets) { int[] f = new int[Math.max(itemsets) + 1]; for (int[] itemset : itemsets) { for (int i : itemset) { f[i]++; } } return f; }
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Returns the frequency of single items. @param itemsets the transaction database. @return the frequency of single items
[ "Returns", "the", "frequency", "of", "single", "items", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/association/FPTree.java#L293-L301
17,219
haifengl/smile
core/src/main/java/smile/association/FPTree.java
FPTree.add
public void add(int[] itemset) { numTransactions++; int m = 0; int t = itemset.length; int[] o = new int[t]; for (int i = 0; i < t; i++) { int item = itemset[i]; o[i] = order[item]; if (itemSupport[item] >= minSupport) { ...
java
public void add(int[] itemset) { numTransactions++; int m = 0; int t = itemset.length; int[] o = new int[t]; for (int i = 0; i < t; i++) { int item = itemset[i]; o[i] = order[item]; if (itemSupport[item] >= minSupport) { ...
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Add an item set into the FP-tree. @param itemset an item set, which should NOT contain duplicated items. Note that it is reordered after the call.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/association/FPTree.java#L316-L349
17,220
haifengl/smile
core/src/main/java/smile/association/FPTree.java
FPTree.add
public void add(int index, int end, int[] itemset, int support) { root.add(index, end, itemset, support); }
java
public void add(int index, int end, int[] itemset, int support) { root.add(index, end, itemset, support); }
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Add an item set into the FP-tree. The items in the set is already in the descending order of frequency. @param index the current item index in the item set. @param end the end index of item set to append into the database. @param itemset an item set. @param support the support/frequency of the item set.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/association/FPTree.java#L359-L361
17,221
haifengl/smile
math/src/main/java/smile/math/distance/HammingDistance.java
HammingDistance.d
@Override public double d(T[] x, T[] y) { if (x.length != y.length) throw new IllegalArgumentException(String.format("Arrays have different length: x[%d], y[%d]", x.length, y.length)); int dist = 0; for (int i = 0; i < x.length; i++) { if (!x[i].equals(y[i])) ...
java
@Override public double d(T[] x, T[] y) { if (x.length != y.length) throw new IllegalArgumentException(String.format("Arrays have different length: x[%d], y[%d]", x.length, y.length)); int dist = 0; for (int i = 0; i < x.length; i++) { if (!x[i].equals(y[i])) ...
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Returns Hamming distance between the two arrays.
[ "Returns", "Hamming", "distance", "between", "the", "two", "arrays", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/math/src/main/java/smile/math/distance/HammingDistance.java#L48-L60
17,222
haifengl/smile
math/src/main/java/smile/math/distance/HammingDistance.java
HammingDistance.d
public static int d(int x, int y) { int dist = 0; int val = x ^ y; // Count the number of set bits (Knuth's algorithm) while (val != 0) { ++dist; val &= val - 1; } return dist; }
java
public static int d(int x, int y) { int dist = 0; int val = x ^ y; // Count the number of set bits (Knuth's algorithm) while (val != 0) { ++dist; val &= val - 1; } return dist; }
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Returns Hamming distance between the two integers.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/math/src/main/java/smile/math/distance/HammingDistance.java#L79-L90
17,223
haifengl/smile
math/src/main/java/smile/math/distance/HammingDistance.java
HammingDistance.d
public static int d(BitSet x, BitSet y) { if (x.size() != y.size()) throw new IllegalArgumentException(String.format("BitSets have different length: x[%d], y[%d]", x.size(), y.size())); int dist = 0; for (int i = 0; i < x.size(); i++) { if (x.get(i) != y.get(i)) ...
java
public static int d(BitSet x, BitSet y) { if (x.size() != y.size()) throw new IllegalArgumentException(String.format("BitSets have different length: x[%d], y[%d]", x.size(), y.size())); int dist = 0; for (int i = 0; i < x.size(); i++) { if (x.get(i) != y.get(i)) ...
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Returns Hamming distance between the two BitSets.
[ "Returns", "Hamming", "distance", "between", "the", "two", "BitSets", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/math/src/main/java/smile/math/distance/HammingDistance.java#L159-L170
17,224
haifengl/smile
plot/src/main/java/smile/plot/Base.java
Base.initBaseCoord
void initBaseCoord() { baseCoords = new double[dimension + 1][]; for (int i = 0; i < baseCoords.length; i++) { baseCoords[i] = lowerBound.clone(); if (i > 0) { baseCoords[i][i - 1] = upperBound[i - 1]; } } }
java
void initBaseCoord() { baseCoords = new double[dimension + 1][]; for (int i = 0; i < baseCoords.length; i++) { baseCoords[i] = lowerBound.clone(); if (i > 0) { baseCoords[i][i - 1] = upperBound[i - 1]; } } }
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Reset coord.
[ "Reset", "coord", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/Base.java#L139-L147
17,225
haifengl/smile
plot/src/main/java/smile/plot/Base.java
Base.setPrecisionUnit
void setPrecisionUnit(int i) { if (upperBound[i] > lowerBound[i]) { double digits = Math.log10(Math.abs(upperBound[i] - lowerBound[i])); double residual = digits - Math.floor(digits); if (residual < 0.2) { // If the range is less than 15 units, we reduce one l...
java
void setPrecisionUnit(int i) { if (upperBound[i] > lowerBound[i]) { double digits = Math.log10(Math.abs(upperBound[i] - lowerBound[i])); double residual = digits - Math.floor(digits); if (residual < 0.2) { // If the range is less than 15 units, we reduce one l...
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Set the precision unit for axis i.
[ "Set", "the", "precision", "unit", "for", "axis", "i", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/Base.java#L159-L179
17,226
haifengl/smile
plot/src/main/java/smile/plot/Base.java
Base.extendBound
public void extendBound(int i) { if (i < 0 || i >= dimension) { throw new IllegalArgumentException("Invalid bound index: " + i); } extendBound[i] = true; lowerBound[i] = precisionUnit[i] * (Math.floor(originalLowerBound[i] / precisionUnit[i])); upperBound[i] = precis...
java
public void extendBound(int i) { if (i < 0 || i >= dimension) { throw new IllegalArgumentException("Invalid bound index: " + i); } extendBound[i] = true; lowerBound[i] = precisionUnit[i] * (Math.floor(originalLowerBound[i] / precisionUnit[i])); upperBound[i] = precis...
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Round the bounds for axis i.
[ "Round", "the", "bounds", "for", "axis", "i", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/Base.java#L184-L192
17,227
haifengl/smile
plot/src/main/java/smile/plot/Base.java
Base.extendLowerBound
public void extendLowerBound(double[] bound) { if (bound.length != dimension) { throw new IllegalArgumentException(BOUND_SIZE_DON_T_MATCH_THE_DIMENSION); } boolean extend = false; for (int i = 0; i < bound.length; i++) { if (bound[i] < originalLowerBound[i]) { ...
java
public void extendLowerBound(double[] bound) { if (bound.length != dimension) { throw new IllegalArgumentException(BOUND_SIZE_DON_T_MATCH_THE_DIMENSION); } boolean extend = false; for (int i = 0; i < bound.length; i++) { if (bound[i] < originalLowerBound[i]) { ...
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Extend lower bounds.
[ "Extend", "lower", "bounds", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/Base.java#L232-L248
17,228
haifengl/smile
plot/src/main/java/smile/plot/Base.java
Base.extendUpperBound
public void extendUpperBound(double[] bound) { if (bound.length != dimension) { throw new IllegalArgumentException(BOUND_SIZE_DON_T_MATCH_THE_DIMENSION); } boolean extend = false; for (int i = 0; i < bound.length; i++) { if (bound[i] > originalUpperBound[i]) { ...
java
public void extendUpperBound(double[] bound) { if (bound.length != dimension) { throw new IllegalArgumentException(BOUND_SIZE_DON_T_MATCH_THE_DIMENSION); } boolean extend = false; for (int i = 0; i < bound.length; i++) { if (bound[i] > originalUpperBound[i]) { ...
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Extend upper bounds.
[ "Extend", "upper", "bounds", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/Base.java#L253-L269
17,229
haifengl/smile
core/src/main/java/smile/clustering/CLARANS.java
CLARANS.getRandomNeighbor
private double getRandomNeighbor(T[] data, T[] medoids, int[] y, double[] d) { int n = data.length; int index = Math.randomInt(k); T medoid = null; boolean dup; do { dup = false; medoid = data[Math.randomInt(n)]; for (int i = 0; i < k; i++) { ...
java
private double getRandomNeighbor(T[] data, T[] medoids, int[] y, double[] d) { int n = data.length; int index = Math.randomInt(k); T medoid = null; boolean dup; do { dup = false; medoid = data[Math.randomInt(n)]; for (int i = 0; i < k; i++) { ...
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Generate a random neighbor which differs in only one medoid with current clusters.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/clustering/CLARANS.java#L230-L270
17,230
haifengl/smile
plot/src/main/java/smile/plot/BoxPlot.java
BoxPlot.init
private void init() { quantiles = new double[data.length][8]; for (int i = 0; i < data.length; i++) { int n = data[i].length; Arrays.sort(data[i]); quantiles[i][1] = data[i][n / 4]; quantiles[i][2] = data[i][n / 2]; quantiles[i][3] = data[i][3 ...
java
private void init() { quantiles = new double[data.length][8]; for (int i = 0; i < data.length; i++) { int n = data[i].length; Arrays.sort(data[i]); quantiles[i][1] = data[i][n / 4]; quantiles[i][2] = data[i][n / 2]; quantiles[i][3] = data[i][3 ...
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Calculate quantiles.
[ "Calculate", "quantiles", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/BoxPlot.java#L109-L123
17,231
haifengl/smile
plot/src/main/java/smile/plot/BoxPlot.java
BoxPlot.plot
public static PlotCanvas plot(double[] data) { double[] lowerBound = {0, Math.min(data)}; double[] upperBound = {1, Math.max(data)}; PlotCanvas canvas = new PlotCanvas(lowerBound, upperBound); canvas.add(new BoxPlot(data)); canvas.getAxis(0).setGridVisible(false); canva...
java
public static PlotCanvas plot(double[] data) { double[] lowerBound = {0, Math.min(data)}; double[] upperBound = {1, Math.max(data)}; PlotCanvas canvas = new PlotCanvas(lowerBound, upperBound); canvas.add(new BoxPlot(data)); canvas.getAxis(0).setGridVisible(false); canva...
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Create a plot canvas with the box plot of given data. @param data a sample set.
[ "Create", "a", "plot", "canvas", "with", "the", "box", "plot", "of", "given", "data", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/BoxPlot.java#L205-L216
17,232
haifengl/smile
plot/src/main/java/smile/plot/BoxPlot.java
BoxPlot.plot
public static PlotCanvas plot(double[][] data, String[] labels) { if (data.length != labels.length) { throw new IllegalArgumentException("Data size and label size don't match."); } double[] lowerBound = {0, Math.min(data)}; double[] upperBound = {data.length, Math.max(data)}...
java
public static PlotCanvas plot(double[][] data, String[] labels) { if (data.length != labels.length) { throw new IllegalArgumentException("Data size and label size don't match."); } double[] lowerBound = {0, Math.min(data)}; double[] upperBound = {data.length, Math.max(data)}...
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Create a plot canvas with multiple box plots of given data. @param data a data matrix of which each row will create a box plot. @param labels the labels for each box plot.
[ "Create", "a", "plot", "canvas", "with", "multiple", "box", "plots", "of", "given", "data", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/BoxPlot.java#L240-L264
17,233
haifengl/smile
core/src/main/java/smile/feature/MaxAbsScaler.java
MaxAbsScaler.transform
@Override public double[] transform(double[] x) { if (x.length != scale.length) { throw new IllegalArgumentException(String.format("Invalid vector size %d, expected %d", x.length, scale.length)); } double[] y = copy ? new double[x.length] : x; for (int i = 0; i < x.lengt...
java
@Override public double[] transform(double[] x) { if (x.length != scale.length) { throw new IllegalArgumentException(String.format("Invalid vector size %d, expected %d", x.length, scale.length)); } double[] y = copy ? new double[x.length] : x; for (int i = 0; i < x.lengt...
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Scales each feature by its maximum absolute value. @param x a vector to be scaled. The vector will be modified on output. @return the input vector.
[ "Scales", "each", "feature", "by", "its", "maximum", "absolute", "value", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/feature/MaxAbsScaler.java#L79-L91
17,234
haifengl/smile
core/src/main/java/smile/classification/DecisionTree.java
DecisionTree.impurity
private double impurity(int[] count, int n) { double impurity = 0.0; switch (rule) { case GINI: impurity = 1.0; for (int i = 0; i < count.length; i++) { if (count[i] > 0) { double p = (double) count[i] / n; ...
java
private double impurity(int[] count, int n) { double impurity = 0.0; switch (rule) { case GINI: impurity = 1.0; for (int i = 0; i < count.length; i++) { if (count[i] > 0) { double p = (double) count[i] / n; ...
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Returns the impurity of a node. @param count the sample count in each class. @param n the number of samples in the node. @return the impurity of a node
[ "Returns", "the", "impurity", "of", "a", "node", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/classification/DecisionTree.java#L742-L776
17,235
haifengl/smile
core/src/main/java/smile/gap/GeneticAlgorithm.java
GeneticAlgorithm.setTournament
public GeneticAlgorithm<T> setTournament(int size, double p) { if (size < 1) { throw new IllegalArgumentException("Invalid tournament size: " + size); } if (p < 0.5 || p > 1.0) { throw new IllegalArgumentException("Invalid best-player-wins probability: " + p); ...
java
public GeneticAlgorithm<T> setTournament(int size, double p) { if (size < 1) { throw new IllegalArgumentException("Invalid tournament size: " + size); } if (p < 0.5 || p > 1.0) { throw new IllegalArgumentException("Invalid best-player-wins probability: " + p); ...
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Set the tournament size and the best-player-wins probability in tournament selection. @param size the size of tournament pool. @param p the best-player-wins probability.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/gap/GeneticAlgorithm.java#L288-L300
17,236
haifengl/smile
core/src/main/java/smile/gap/GeneticAlgorithm.java
GeneticAlgorithm.evolve
public T evolve(int generation, double threshold) { if (generation <= 0) { throw new IllegalArgumentException("Invalid number of generations to go: " + generation); } // Calculate the fitness of each chromosome. try { MulticoreExecutor.run(tasks); ...
java
public T evolve(int generation, double threshold) { if (generation <= 0) { throw new IllegalArgumentException("Invalid number of generations to go: " + generation); } // Calculate the fitness of each chromosome. try { MulticoreExecutor.run(tasks); ...
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Performs genetic algorithm until the given number of generations is reached or the best fitness is larger than the given threshold. @param generation the maximum number of iterations. @param threshold the fitness threshold. The algorithm stops when a solution is found that satisfies minimum criteria. @return the best ...
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/gap/GeneticAlgorithm.java#L356-L422
17,237
haifengl/smile
core/src/main/java/smile/gap/GeneticAlgorithm.java
GeneticAlgorithm.select
@SuppressWarnings("unchecked") private T select(T[] population) { double worst = population[0].fitness(); double[] fitness = new double[size]; switch (selection) { case ROULETTE_WHEEL: if (worst > 0.0) { worst = 0.0; } ...
java
@SuppressWarnings("unchecked") private T select(T[] population) { double worst = population[0].fitness(); double[] fitness = new double[size]; switch (selection) { case ROULETTE_WHEEL: if (worst > 0.0) { worst = 0.0; } ...
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Select a chromosome with replacement from the population based on their fitness. Note that the population should be in ascending order in terms of fitness.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/gap/GeneticAlgorithm.java#L429-L486
17,238
haifengl/smile
core/src/main/java/smile/sequence/HMM.java
HMM.logp
public double logp(int[] o, int[] s) { if (o.length != s.length) { throw new IllegalArgumentException("The observation sequence and state sequence are not the same length."); } int n = s.length; double p = log(pi[s[0]]) + log(b[s[0]][o[0]]); for (int i = 1; i < n; i+...
java
public double logp(int[] o, int[] s) { if (o.length != s.length) { throw new IllegalArgumentException("The observation sequence and state sequence are not the same length."); } int n = s.length; double p = log(pi[s[0]]) + log(b[s[0]][o[0]]); for (int i = 1; i < n; i+...
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Returns the log joint probability of an observation sequence along a state sequence given this HMM. @param o an observation sequence. @param s a state sequence. @return the log joint probability P(o, s | H) given the model H.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/sequence/HMM.java#L246-L258
17,239
haifengl/smile
core/src/main/java/smile/sequence/HMM.java
HMM.logp
public double logp(int[] o) { double[][] alpha = new double[o.length][numStates]; double[] scaling = new double[o.length]; forward(o, alpha, scaling); double p = 0.0; for (int t = 0; t < o.length; t++) { p += java.lang.Math.log(scaling[t]); } return...
java
public double logp(int[] o) { double[][] alpha = new double[o.length][numStates]; double[] scaling = new double[o.length]; forward(o, alpha, scaling); double p = 0.0; for (int t = 0; t < o.length; t++) { p += java.lang.Math.log(scaling[t]); } return...
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Returns the logarithm probability of an observation sequence given this HMM. A scaling procedure is used in order to avoid underflows when computing the probability of long sequences. @param o an observation sequence. @return the log probability of this sequence.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/sequence/HMM.java#L278-L290
17,240
haifengl/smile
core/src/main/java/smile/sequence/HMM.java
HMM.forward
private void forward(int[] o, double[][] alpha, double[] scaling) { for (int k = 0; k < numStates; k++) { alpha[0][k] = pi[k] * b[k][o[0]]; } scale(scaling, alpha, 0); for (int t = 1; t < o.length; t++) { for (int k = 0; k < numStates; k++) { doub...
java
private void forward(int[] o, double[][] alpha, double[] scaling) { for (int k = 0; k < numStates; k++) { alpha[0][k] = pi[k] * b[k][o[0]]; } scale(scaling, alpha, 0); for (int t = 1; t < o.length; t++) { for (int k = 0; k < numStates; k++) { doub...
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Scaled forward procedure without underflow. @param o an observation sequence. @param alpha on output, alpha(i, j) holds the scaled total probability of ending up in state i at time j. @param scaling on output, it holds scaling factors.
[ "Scaled", "forward", "procedure", "without", "underflow", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/sequence/HMM.java#L317-L335
17,241
haifengl/smile
core/src/main/java/smile/sequence/HMM.java
HMM.backward
private void backward(int[] o, double[][] beta, double[] scaling) { int n = o.length - 1; for (int i = 0; i < numStates; i++) { beta[n][i] = 1.0 / scaling[n]; } for (int t = n; t-- > 0;) { for (int i = 0; i < numStates; i++) { double sum = 0.; ...
java
private void backward(int[] o, double[][] beta, double[] scaling) { int n = o.length - 1; for (int i = 0; i < numStates; i++) { beta[n][i] = 1.0 / scaling[n]; } for (int t = n; t-- > 0;) { for (int i = 0; i < numStates; i++) { double sum = 0.; ...
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Scaled backward procedure without underflow. @param o an observation sequence. @param beta on output, beta(i, j) holds the scaled total probability of starting up in state i at time j. @param scaling on input, it should hold scaling factors computed by forward procedure.
[ "Scaled", "backward", "procedure", "without", "underflow", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/sequence/HMM.java#L346-L363
17,242
haifengl/smile
core/src/main/java/smile/taxonomy/Concept.java
Concept.addKeyword
public void addKeyword(String keyword) { if (taxonomy.concepts.containsKey(keyword)) { throw new IllegalArgumentException(String.format("Concept %s already exists.", keyword)); } taxonomy.concepts.put(keyword, this); if (synset == null) { synset = new TreeSet<>(...
java
public void addKeyword(String keyword) { if (taxonomy.concepts.containsKey(keyword)) { throw new IllegalArgumentException(String.format("Concept %s already exists.", keyword)); } taxonomy.concepts.put(keyword, this); if (synset == null) { synset = new TreeSet<>(...
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Add a keyword to the concept synset.
[ "Add", "a", "keyword", "to", "the", "concept", "synset", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/taxonomy/Concept.java#L195-L207
17,243
haifengl/smile
core/src/main/java/smile/taxonomy/Concept.java
Concept.addKeywords
public void addKeywords(String[] keywords) { for (String keyword : keywords) { if (taxonomy.concepts.containsKey(keyword)) { throw new IllegalArgumentException(String.format("Concept %s already exists.", keyword)); } } for (String keyword : keywords) { ...
java
public void addKeywords(String[] keywords) { for (String keyword : keywords) { if (taxonomy.concepts.containsKey(keyword)) { throw new IllegalArgumentException(String.format("Concept %s already exists.", keyword)); } } for (String keyword : keywords) { ...
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Add a list of synomym to the concept synset.
[ "Add", "a", "list", "of", "synomym", "to", "the", "concept", "synset", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/taxonomy/Concept.java#L212-L230
17,244
haifengl/smile
core/src/main/java/smile/taxonomy/Concept.java
Concept.removeKeyword
public void removeKeyword(String keyword) { if (!taxonomy.concepts.containsKey(keyword)) { throw new IllegalArgumentException(String.format("Concept %s does not exist.", keyword)); } taxonomy.concepts.remove(keyword); if (synset != null) { synset.remove(keyword);...
java
public void removeKeyword(String keyword) { if (!taxonomy.concepts.containsKey(keyword)) { throw new IllegalArgumentException(String.format("Concept %s does not exist.", keyword)); } taxonomy.concepts.remove(keyword); if (synset != null) { synset.remove(keyword);...
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Remove a keyword from the concept synset.
[ "Remove", "a", "keyword", "from", "the", "concept", "synset", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/taxonomy/Concept.java#L256-L265
17,245
haifengl/smile
core/src/main/java/smile/taxonomy/Concept.java
Concept.addChild
public void addChild(Concept concept) { if (taxonomy != concept.taxonomy) { throw new IllegalArgumentException("Concepts are not from the same taxonomy."); } if (children == null) { children = new ArrayList<>(); } children.add(concept); c...
java
public void addChild(Concept concept) { if (taxonomy != concept.taxonomy) { throw new IllegalArgumentException("Concepts are not from the same taxonomy."); } if (children == null) { children = new ArrayList<>(); } children.add(concept); c...
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Add a child to this node
[ "Add", "a", "child", "to", "this", "node" ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/taxonomy/Concept.java#L287-L298
17,246
haifengl/smile
core/src/main/java/smile/taxonomy/Concept.java
Concept.removeChild
public boolean removeChild(Concept concept) { if (concept.parent != this) { throw new IllegalArgumentException("Concept to remove is not a child"); } for (int i = 0; i < children.size(); i++) { if (children.get(i) == concept) { children.remove(i); ...
java
public boolean removeChild(Concept concept) { if (concept.parent != this) { throw new IllegalArgumentException("Concept to remove is not a child"); } for (int i = 0; i < children.size(); i++) { if (children.get(i) == concept) { children.remove(i); ...
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Remove a child to this node
[ "Remove", "a", "child", "to", "this", "node" ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/taxonomy/Concept.java#L303-L317
17,247
haifengl/smile
core/src/main/java/smile/taxonomy/Concept.java
Concept.isAncestorOf
public boolean isAncestorOf(Concept concept) { Concept p = concept.parent; while (p != null) { if (p == this) { return true; } else { p = p.parent; } } return false; }
java
public boolean isAncestorOf(Concept concept) { Concept p = concept.parent; while (p != null) { if (p == this) { return true; } else { p = p.parent; } } return false; }
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Returns true if this concept is an ancestor of the given concept.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/taxonomy/Concept.java#L322-L334
17,248
haifengl/smile
core/src/main/java/smile/taxonomy/Concept.java
Concept.getPathFromRoot
public List<Concept> getPathFromRoot() { LinkedList<Concept> path = new LinkedList<>(); Concept node = this; while (node != null) { path.addFirst(node); node = node.parent; } return path; }
java
public List<Concept> getPathFromRoot() { LinkedList<Concept> path = new LinkedList<>(); Concept node = this; while (node != null) { path.addFirst(node); node = node.parent; } return path; }
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Returns the path from root to the given node.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/taxonomy/Concept.java#L339-L349
17,249
haifengl/smile
core/src/main/java/smile/taxonomy/Concept.java
Concept.getPathToRoot
public List<Concept> getPathToRoot() { LinkedList<Concept> path = new LinkedList<>(); Concept node = this; while (node != null) { path.add(node); node = node.parent; } return path; }
java
public List<Concept> getPathToRoot() { LinkedList<Concept> path = new LinkedList<>(); Concept node = this; while (node != null) { path.add(node); node = node.parent; } return path; }
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Returns the path from the given node to the root.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/taxonomy/Concept.java#L354-L364
17,250
haifengl/smile
core/src/main/java/smile/sequence/CRF.java
CRF.featureset
public double[] featureset(double[] features, int label) { double[] fs = new double[features.length + 1]; System.arraycopy(features, 0, fs, 0, features.length); fs[features.length] = label; return fs; }
java
public double[] featureset(double[] features, int label) { double[] fs = new double[features.length + 1]; System.arraycopy(features, 0, fs, 0, features.length); fs[features.length] = label; return fs; }
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Returns a feature set with the class label of previous position. @param features the indices of the nonzero features. @param label the class label of previous position as a feature.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/sequence/CRF.java#L88-L93
17,251
haifengl/smile
core/src/main/java/smile/sequence/CRF.java
CRF.predictForwardBackward
private int[] predictForwardBackward(int[][] x) { int n = x.length; // length of sequence TrellisNode[][] trellis = getTrellis(x); double[] scaling = new double[n]; forward(trellis, scaling); backward(trellis); int[] label = new int[n]; double[] p = new double[n...
java
private int[] predictForwardBackward(int[][] x) { int n = x.length; // length of sequence TrellisNode[][] trellis = getTrellis(x); double[] scaling = new double[n]; forward(trellis, scaling); backward(trellis); int[] label = new int[n]; double[] p = new double[n...
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Returns the most likely label sequence given the feature sequence by the forward-backward algorithm. @param x a sequence of sparse features taking values in [0, p) about each position of original sequence, where p is the number of features. @return the most likely label sequence.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/sequence/CRF.java#L386-L413
17,252
haifengl/smile
core/src/main/java/smile/sequence/CRF.java
CRF.predictViterbi
private int[] predictViterbi(int[][] x) { int n = x.length; double[][] trellis = new double[n][numClasses]; int[][] psy = new int[n][numClasses]; int p = x[0].length; // dimension // forward double[] t0 = trellis[0]; int[] p0 = psy[0]; int[] features = ...
java
private int[] predictViterbi(int[][] x) { int n = x.length; double[][] trellis = new double[n][numClasses]; int[][] psy = new int[n][numClasses]; int p = x[0].length; // dimension // forward double[] t0 = trellis[0]; int[] p0 = psy[0]; int[] features = ...
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Returns the most likely label sequence given the feature sequence by the Viterbi algorithm. @param x a sequence of sparse features taking values in [0, p) about each position of original sequence, where p is the number of features. @return the most likely label sequence.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/sequence/CRF.java#L423-L476
17,253
haifengl/smile
core/src/main/java/smile/sequence/CRF.java
CRF.backward
private void backward(TrellisNode[][] trellis) { int n = trellis.length - 1; TrellisNode[] tn = trellis[n]; for (int i = 0; i < numClasses; i++) { tn[i].beta = 1.0; } for (int t = n; t-- > 0;) { TrellisNode[] tt = trellis[t]; TrellisNode[] tt1...
java
private void backward(TrellisNode[][] trellis) { int n = trellis.length - 1; TrellisNode[] tn = trellis[n]; for (int i = 0; i < numClasses; i++) { tn[i].beta = 1.0; } for (int t = n; t-- > 0;) { TrellisNode[] tt = trellis[t]; TrellisNode[] tt1...
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Performs backward procedure on the trellis.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/sequence/CRF.java#L860-L887
17,254
haifengl/smile
core/src/main/java/smile/sequence/CRF.java
CRF.setTargets
private void setTargets(TrellisNode[][] trellis, double[] scaling, int[] label) { TrellisNode[] t0 = trellis[0]; // Finding the normalizer for our first 'column' in the matrix double normalizer = 0.0; for (int i = 0; i < numClasses; i++) { normalizer += t0[i].expScores[0] * ...
java
private void setTargets(TrellisNode[][] trellis, double[] scaling, int[] label) { TrellisNode[] t0 = trellis[0]; // Finding the normalizer for our first 'column' in the matrix double normalizer = 0.0; for (int i = 0; i < numClasses; i++) { normalizer += t0[i].expScores[0] * ...
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Set training targets based on results of forward-backward
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/sequence/CRF.java#L954-L991
17,255
haifengl/smile
core/src/main/java/smile/clustering/HierarchicalClustering.java
HierarchicalClustering.partition
public int[] partition(int k) { int n = merge.length + 1; int[] membership = new int[n]; IntHeapSelect heap = new IntHeapSelect(k); for (int i = 2; i <= k; i++) { heap.add(merge[n - i][0]); heap.add(merge[n - i][1]); } for (int i = 0; i < k; i++)...
java
public int[] partition(int k) { int n = merge.length + 1; int[] membership = new int[n]; IntHeapSelect heap = new IntHeapSelect(k); for (int i = 2; i <= k; i++) { heap.add(merge[n - i][0]); heap.add(merge[n - i][1]); } for (int i = 0; i < k; i++)...
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Cuts a tree into several groups by specifying the desired number. @param k the number of clusters. @return the cluster label of each sample.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/clustering/HierarchicalClustering.java#L136-L151
17,256
haifengl/smile
core/src/main/java/smile/clustering/HierarchicalClustering.java
HierarchicalClustering.partition
public int[] partition(double h) { for (int i = 0; i < height.length - 1; i++) { if (height[i] > height[i + 1]) { throw new IllegalStateException("Non-monotonic cluster tree -- the linkage is probably not appropriate!"); } } int n = merge.length + 1; ...
java
public int[] partition(double h) { for (int i = 0; i < height.length - 1; i++) { if (height[i] > height[i + 1]) { throw new IllegalStateException("Non-monotonic cluster tree -- the linkage is probably not appropriate!"); } } int n = merge.length + 1; ...
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Cuts a tree into several groups by specifying the cut height. @param h the cut height. @return the cluster label of each sample.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/clustering/HierarchicalClustering.java#L158-L178
17,257
haifengl/smile
core/src/main/java/smile/clustering/HierarchicalClustering.java
HierarchicalClustering.bfs
private void bfs(int[] membership, int cluster, int id) { int n = merge.length + 1; Queue<Integer> queue = new LinkedList<>(); queue.offer(cluster); for (Integer i = queue.poll(); i != null; i = queue.poll()) { if (i < n) { membership[i] = id; ...
java
private void bfs(int[] membership, int cluster, int id) { int n = merge.length + 1; Queue<Integer> queue = new LinkedList<>(); queue.offer(cluster); for (Integer i = queue.poll(); i != null; i = queue.poll()) { if (i < n) { membership[i] = id; ...
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BFS the merge tree and identify cluster membership. @param membership the cluster membership array. @param cluster the last merge point of cluster. @param id the cluster ID.
[ "BFS", "the", "merge", "tree", "and", "identify", "cluster", "membership", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/clustering/HierarchicalClustering.java#L186-L215
17,258
haifengl/smile
nlp/src/main/java/smile/nlp/stemmer/PorterStemmer.java
PorterStemmer.vowelinstem
private final boolean vowelinstem() { int i; for (i = 0; i <= j; i++) { if (!isConsonant(i)) { return true; } } return false; }
java
private final boolean vowelinstem() { int i; for (i = 0; i <= j; i++) { if (!isConsonant(i)) { return true; } } return false; }
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Returns true if 0,...j contains a vowel
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/nlp/src/main/java/smile/nlp/stemmer/PorterStemmer.java#L154-L162
17,259
haifengl/smile
nlp/src/main/java/smile/nlp/stemmer/PorterStemmer.java
PorterStemmer.stripPluralParticiple
public String stripPluralParticiple(String word) { b = word.toCharArray(); k = word.length() - 1; if (k > 1 && !word.equalsIgnoreCase("is") && !word.equalsIgnoreCase("was") && !word.equalsIgnoreCase("has") && !word.equalsIgnoreCase("his") && !word.equalsIgnoreCase("this")) { step1(t...
java
public String stripPluralParticiple(String word) { b = word.toCharArray(); k = word.length() - 1; if (k > 1 && !word.equalsIgnoreCase("is") && !word.equalsIgnoreCase("was") && !word.equalsIgnoreCase("has") && !word.equalsIgnoreCase("his") && !word.equalsIgnoreCase("this")) { step1(t...
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Remove plurals and participles.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/nlp/src/main/java/smile/nlp/stemmer/PorterStemmer.java#L605-L615
17,260
haifengl/smile
core/src/main/java/smile/classification/NeuralNetwork.java
NeuralNetwork.natural
private static ActivationFunction natural(ErrorFunction error, int k) { if (error == ErrorFunction.CROSS_ENTROPY) { if (k == 1) { return ActivationFunction.LOGISTIC_SIGMOID; } else { return ActivationFunction.SOFTMAX; } } else { ...
java
private static ActivationFunction natural(ErrorFunction error, int k) { if (error == ErrorFunction.CROSS_ENTROPY) { if (k == 1) { return ActivationFunction.LOGISTIC_SIGMOID; } else { return ActivationFunction.SOFTMAX; } } else { ...
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Returns the activation function of output layer based on natural pairing. @param error the error function. @param k the number of output nodes. @return the activation function of output layer based on natural pairing
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/classification/NeuralNetwork.java#L400-L411
17,261
haifengl/smile
core/src/main/java/smile/classification/NeuralNetwork.java
NeuralNetwork.setInput
private void setInput(double[] x) { if (x.length != inputLayer.units) { throw new IllegalArgumentException(String.format("Invalid input vector size: %d, expected: %d", x.length, inputLayer.units)); } System.arraycopy(x, 0, inputLayer.output, 0, inputLayer.units); }
java
private void setInput(double[] x) { if (x.length != inputLayer.units) { throw new IllegalArgumentException(String.format("Invalid input vector size: %d, expected: %d", x.length, inputLayer.units)); } System.arraycopy(x, 0, inputLayer.output, 0, inputLayer.units); }
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Sets the input vector into the input layer. @param x the input vector.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/classification/NeuralNetwork.java#L597-L602
17,262
haifengl/smile
core/src/main/java/smile/classification/NeuralNetwork.java
NeuralNetwork.getOutput
private void getOutput(double[] y) { if (y.length != outputLayer.units) { throw new IllegalArgumentException(String.format("Invalid output vector size: %d, expected: %d", y.length, outputLayer.units)); } System.arraycopy(outputLayer.output, 0, y, 0, outputLayer.units); }
java
private void getOutput(double[] y) { if (y.length != outputLayer.units) { throw new IllegalArgumentException(String.format("Invalid output vector size: %d, expected: %d", y.length, outputLayer.units)); } System.arraycopy(outputLayer.output, 0, y, 0, outputLayer.units); }
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Returns the output vector into the given array. @param y the output vector.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/classification/NeuralNetwork.java#L608-L613
17,263
haifengl/smile
core/src/main/java/smile/classification/NeuralNetwork.java
NeuralNetwork.softmax
private void softmax() { double max = Double.NEGATIVE_INFINITY; for (int i = 0; i < outputLayer.units; i++) { if (outputLayer.output[i] > max) { max = outputLayer.output[i]; } } double sum = 0.0; for (int i = 0; i < outputLayer.units; i++)...
java
private void softmax() { double max = Double.NEGATIVE_INFINITY; for (int i = 0; i < outputLayer.units; i++) { if (outputLayer.output[i] > max) { max = outputLayer.output[i]; } } double sum = 0.0; for (int i = 0; i < outputLayer.units; i++)...
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Calculate softmax activation function in output layer without overflow.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/classification/NeuralNetwork.java#L646-L664
17,264
haifengl/smile
core/src/main/java/smile/classification/NeuralNetwork.java
NeuralNetwork.propagate
private void propagate() { for (int l = 0; l < net.length - 1; l++) { propagate(net[l], net[l + 1]); } }
java
private void propagate() { for (int l = 0; l < net.length - 1; l++) { propagate(net[l], net[l + 1]); } }
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Propagates the signals through the neural network.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/classification/NeuralNetwork.java#L669-L673
17,265
haifengl/smile
core/src/main/java/smile/classification/NeuralNetwork.java
NeuralNetwork.backpropagate
private void backpropagate() { for (int l = net.length; --l > 0;) { backpropagate(net[l], net[l - 1]); } }
java
private void backpropagate() { for (int l = net.length; --l > 0;) { backpropagate(net[l], net[l - 1]); } }
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Propagates the errors back through the network.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/classification/NeuralNetwork.java#L752-L756
17,266
haifengl/smile
core/src/main/java/smile/classification/NeuralNetwork.java
NeuralNetwork.adjustWeights
private void adjustWeights() { for (int l = 1; l < net.length; l++) { for (int i = 0; i < net[l].units; i++) { for (int j = 0; j <= net[l - 1].units; j++) { double out = net[l - 1].output[j]; double err = net[l].error[i]; do...
java
private void adjustWeights() { for (int l = 1; l < net.length; l++) { for (int i = 0; i < net[l].units; i++) { for (int j = 0; j <= net[l - 1].units; j++) { double out = net[l - 1].output[j]; double err = net[l].error[i]; do...
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Adjust network weights by back-propagation algorithm.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/classification/NeuralNetwork.java#L761-L776
17,267
haifengl/smile
core/src/main/java/smile/classification/NeuralNetwork.java
NeuralNetwork.predict
@Override public int predict(double[] x, double[] y) { setInput(x); propagate(); getOutput(y); if (outputLayer.units == 1) { if (outputLayer.output[0] > 0.5) { return 0; } else { return 1; } } doubl...
java
@Override public int predict(double[] x, double[] y) { setInput(x); propagate(); getOutput(y); if (outputLayer.units == 1) { if (outputLayer.output[0] > 0.5) { return 0; } else { return 1; } } doubl...
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Predict the target value of a given instance. Note that this method is NOT multi-thread safe. @param x the instance. @param y the array to store network output on output. For softmax activation function, these are estimated posteriori probabilities. @return the predicted class label.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/classification/NeuralNetwork.java#L786-L809
17,268
haifengl/smile
core/src/main/java/smile/classification/NeuralNetwork.java
NeuralNetwork.learn
public double learn(double[] x, double[] y, double weight) { setInput(x); propagate(); double err = weight * computeOutputError(y); if (weight != 1.0) { for (int i = 0; i < outputLayer.units; i++) { outputLayer.error[i] *= weight; } } ...
java
public double learn(double[] x, double[] y, double weight) { setInput(x); propagate(); double err = weight * computeOutputError(y); if (weight != 1.0) { for (int i = 0; i < outputLayer.units; i++) { outputLayer.error[i] *= weight; } } ...
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Update the neural network with given instance and associated target value. Note that this method is NOT multi-thread safe. @param x the training instance. @param y the target value. @param weight a positive weight value associated with the training instance. @return the weighted training error before back-propagation.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/classification/NeuralNetwork.java#L849-L864
17,269
haifengl/smile
core/src/main/java/smile/classification/NeuralNetwork.java
NeuralNetwork.learn
public void learn(double[] x, int y, double weight) { if (weight < 0.0) { throw new IllegalArgumentException("Invalid weight: " + weight); } if (weight == 0.0) { logger.info("Ignore the training instance with zero weight."); return; } ...
java
public void learn(double[] x, int y, double weight) { if (weight < 0.0) { throw new IllegalArgumentException("Invalid weight: " + weight); } if (weight == 0.0) { logger.info("Ignore the training instance with zero weight."); return; } ...
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Online update the neural network with a new training instance. Note that this method is NOT multi-thread safe. @param x training instance. @param y training label. @param weight a positive weight value associated with the training instance.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/classification/NeuralNetwork.java#L879-L922
17,270
haifengl/smile
core/src/main/java/smile/classification/NeuralNetwork.java
NeuralNetwork.learn
public void learn(double[][] x, int[] y) { int n = x.length; int[] index = Math.permutate(n); for (int i = 0; i < n; i++) { learn(x[index[i]], y[index[i]]); } }
java
public void learn(double[][] x, int[] y) { int n = x.length; int[] index = Math.permutate(n); for (int i = 0; i < n; i++) { learn(x[index[i]], y[index[i]]); } }
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Trains the neural network with the given dataset for one epoch by stochastic gradient descent. @param x training instances. @param y training labels in [0, k), where k is the number of classes.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/classification/NeuralNetwork.java#L931-L937
17,271
haifengl/smile
plot/src/main/java/smile/plot/Grid.java
Grid.plot
public static PlotCanvas plot(String id, double[][][] data) { double[] lowerBound = {data[0][0][0], data[0][0][1]}; double[] upperBound = {data[0][0][0], data[0][0][1]}; for (int i = 0; i < data.length; i++) { for (int j = 0; j < data[i].length; j++) { if (data[i][j][...
java
public static PlotCanvas plot(String id, double[][][] data) { double[] lowerBound = {data[0][0][0], data[0][0][1]}; double[] upperBound = {data[0][0][0], data[0][0][1]}; for (int i = 0; i < data.length; i++) { for (int j = 0; j < data[i].length; j++) { if (data[i][j][...
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Create a 2D grid plot canvas. @param id the id of the plot. @param data an m x n x 2 array which are coordinates of m x n grid.
[ "Create", "a", "2D", "grid", "plot", "canvas", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/Grid.java#L113-L140
17,272
haifengl/smile
demo/src/main/java/smile/demo/projection/LDADemo.java
LDADemo.learn
public JComponent learn() { double[][] data = dataset[datasetIndex].toArray(new double[dataset[datasetIndex].size()][]); String[] names = dataset[datasetIndex].toArray(new String[dataset[datasetIndex].size()]); if (names[0] == null) { names = null; } int[] l...
java
public JComponent learn() { double[][] data = dataset[datasetIndex].toArray(new double[dataset[datasetIndex].size()][]); String[] names = dataset[datasetIndex].toArray(new String[dataset[datasetIndex].size()]); if (names[0] == null) { names = null; } int[] l...
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Execute the projection algorithm and return a swing JComponent representing the clusters.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/demo/src/main/java/smile/demo/projection/LDADemo.java#L90-L124
17,273
haifengl/smile
math/src/main/java/smile/math/matrix/EVD.java
EVD.getD
public DenseMatrix getD() { int n = V.nrows(); DenseMatrix D = Matrix.zeros(n, n); for (int i = 0; i < n; i++) { D.set(i, i, d[i]); if (e != null) { if (e[i] > 0) { D.set(i, i + 1, e[i]); } else if (e[i] < 0) { ...
java
public DenseMatrix getD() { int n = V.nrows(); DenseMatrix D = Matrix.zeros(n, n); for (int i = 0; i < n; i++) { D.set(i, i, d[i]); if (e != null) { if (e[i] > 0) { D.set(i, i + 1, e[i]); } else if (e[i] < 0) { ...
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Returns the block diagonal eigenvalue matrix whose diagonal are the real part of eigenvalues, lower subdiagonal are positive imaginary parts, and upper subdiagonal are negative imaginary parts.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/math/src/main/java/smile/math/matrix/EVD.java#L153-L167
17,274
haifengl/smile
plot/src/main/java/smile/plot/Palette.java
Palette.terrain
public static Color[] terrain(int n, float alpha) { int k = n / 2; float[] H = {4 / 12f, 2 / 12f, 0 / 12f}; float[] S = {1f, 1f, 0f}; float[] V = {0.65f, 0.9f, 0.95f}; Color[] palette = new Color[n]; float h = H[0]; float hw = (H[1] - H[0]) / (k - 1); f...
java
public static Color[] terrain(int n, float alpha) { int k = n / 2; float[] H = {4 / 12f, 2 / 12f, 0 / 12f}; float[] S = {1f, 1f, 0f}; float[] V = {0.65f, 0.9f, 0.95f}; Color[] palette = new Color[n]; float h = H[0]; float hw = (H[1] - H[0]) / (k - 1); f...
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Generate terrain color palette. @param n the number of colors in the palette. @param alpha the parameter in [0,1] for transparency.
[ "Generate", "terrain", "color", "palette", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/Palette.java#L129-L174
17,275
haifengl/smile
plot/src/main/java/smile/plot/Palette.java
Palette.topo
public static Color[] topo(int n, float alpha) { int j = n / 3; int k = n / 3; int i = n - j - k; Color[] palette = new Color[n]; float h = 43 / 60.0f; float hw = (31 / 60.0f - h) / (i - 1); int l = 0; for (; l < i; l++) { palette[l] = hsv(h,...
java
public static Color[] topo(int n, float alpha) { int j = n / 3; int k = n / 3; int i = n - j - k; Color[] palette = new Color[n]; float h = 43 / 60.0f; float hw = (31 / 60.0f - h) / (i - 1); int l = 0; for (; l < i; l++) { palette[l] = hsv(h,...
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Generate topo color palette. @param n the number of colors in the palette. @param alpha the parameter in [0,1] for transparency.
[ "Generate", "topo", "color", "palette", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/Palette.java#L189-L222
17,276
haifengl/smile
plot/src/main/java/smile/plot/Palette.java
Palette.jet
public static Color[] jet(int n, float alpha) { int m = (int) Math.ceil(n / 4); float[] u = new float[3 * m]; for (int i = 0; i < u.length; i++) { if (i == 0) { u[i] = 0.0f; } else if (i <= m) { u[i] = i / (float) m; } else if ...
java
public static Color[] jet(int n, float alpha) { int m = (int) Math.ceil(n / 4); float[] u = new float[3 * m]; for (int i = 0; i < u.length; i++) { if (i == 0) { u[i] = 0.0f; } else if (i <= m) { u[i] = i / (float) m; } else if ...
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Generate jet color palette. @param n the number of colors in the palette. @param alpha the parameter in [0,1] for transparency.
[ "Generate", "jet", "color", "palette", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/Palette.java#L237-L277
17,277
haifengl/smile
plot/src/main/java/smile/plot/Palette.java
Palette.redgreen
public static Color[] redgreen(int n, float alpha) { Color[] palette = new Color[n]; for (int i = 0; i < n; i++) { palette[i] = new Color((float) Math.sqrt((i + 1.0f) / n), (float) Math.sqrt(1 - (i + 1.0f) / n), 0.0f, alpha); } return palette; }
java
public static Color[] redgreen(int n, float alpha) { Color[] palette = new Color[n]; for (int i = 0; i < n; i++) { palette[i] = new Color((float) Math.sqrt((i + 1.0f) / n), (float) Math.sqrt(1 - (i + 1.0f) / n), 0.0f, alpha); } return palette; }
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Generate red-green color palette. @param n the number of colors in the palette. @param alpha the parameter in [0,1] for transparency.
[ "Generate", "red", "-", "green", "color", "palette", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/Palette.java#L292-L299
17,278
haifengl/smile
plot/src/main/java/smile/plot/Palette.java
Palette.redblue
public static Color[] redblue(int n, float alpha) { Color[] palette = new Color[n]; for (int i = 0; i < n; i++) { palette[i] = new Color((float) Math.sqrt((i + 1.0f) / n), 0.0f, (float) Math.sqrt(1 - (i + 1.0f) / n), alpha); } return palette; }
java
public static Color[] redblue(int n, float alpha) { Color[] palette = new Color[n]; for (int i = 0; i < n; i++) { palette[i] = new Color((float) Math.sqrt((i + 1.0f) / n), 0.0f, (float) Math.sqrt(1 - (i + 1.0f) / n), alpha); } return palette; }
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Generate red-blue color palette. @param n the number of colors in the palette. @param alpha the parameter in [0,1] for transparency.
[ "Generate", "red", "-", "blue", "color", "palette", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/Palette.java#L314-L321
17,279
haifengl/smile
plot/src/main/java/smile/plot/Palette.java
Palette.heat
public static Color[] heat(int n, float alpha) { int j = n / 4; int k = n - j; float h = 1.0f / 6; Color[] c = rainbow(k, 0, h, alpha); Color[] palette = new Color[n]; System.arraycopy(c, 0, palette, 0, k); float s = 1 - 1.0f / (2 * j); float end = 1.0f...
java
public static Color[] heat(int n, float alpha) { int j = n / 4; int k = n - j; float h = 1.0f / 6; Color[] c = rainbow(k, 0, h, alpha); Color[] palette = new Color[n]; System.arraycopy(c, 0, palette, 0, k); float s = 1 - 1.0f / (2 * j); float end = 1.0f...
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Generate heat color palette. @param n the number of colors in the palette. @param alpha the parameter in [0,1] for transparency.
[ "Generate", "heat", "color", "palette", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/Palette.java#L336-L356
17,280
haifengl/smile
plot/src/main/java/smile/plot/Palette.java
Palette.hsv
private static Color hsv(float h, float s, float v, float alpha) { float r = 0; float g = 0; float b = 0; if (s == 0) { // this color in on the black white center line <=> h = UNDEFINED // Achromatic color, there is no hue r = v; g = v; ...
java
private static Color hsv(float h, float s, float v, float alpha) { float r = 0; float g = 0; float b = 0; if (s == 0) { // this color in on the black white center line <=> h = UNDEFINED // Achromatic color, there is no hue r = v; g = v; ...
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Generate a color based on HSV model.
[ "Generate", "a", "color", "based", "on", "HSV", "model", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/plot/Palette.java#L410-L476
17,281
haifengl/smile
nlp/src/main/java/smile/nlp/pos/HMMPOSTagger.java
HMMPOSTagger.getDefault
public static HMMPOSTagger getDefault() { if (DEFAULT_TAGGER == null) { try { ObjectInputStream ois = new ObjectInputStream(HMMPOSTagger.class.getResourceAsStream("/smile/nlp/pos/hmmpostagger.model")); DEFAULT_TAGGER = (HMMPOSTagger) ois.readObject(); ...
java
public static HMMPOSTagger getDefault() { if (DEFAULT_TAGGER == null) { try { ObjectInputStream ois = new ObjectInputStream(HMMPOSTagger.class.getResourceAsStream("/smile/nlp/pos/hmmpostagger.model")); DEFAULT_TAGGER = (HMMPOSTagger) ois.readObject(); ...
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Returns the default English POS tagger. @return the default English POS tagger
[ "Returns", "the", "default", "English", "POS", "tagger", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/nlp/src/main/java/smile/nlp/pos/HMMPOSTagger.java#L117-L128
17,282
haifengl/smile
nlp/src/main/java/smile/nlp/pos/HMMPOSTagger.java
HMMPOSTagger.translate
private static int[] translate(PennTreebankPOS[] tags) { int[] seq = new int[tags.length]; for (int i = 0; i < tags.length; i++) { seq[i] = tags[i].ordinal(); } return seq; }
java
private static int[] translate(PennTreebankPOS[] tags) { int[] seq = new int[tags.length]; for (int i = 0; i < tags.length; i++) { seq[i] = tags[i].ordinal(); } return seq; }
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Translate a POS tag sequence to internal representation.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/nlp/src/main/java/smile/nlp/pos/HMMPOSTagger.java#L262-L270
17,283
haifengl/smile
nlp/src/main/java/smile/nlp/pos/HMMPOSTagger.java
HMMPOSTagger.load
public static void load(String dir, List<String[]> sentences, List<PennTreebankPOS[]> labels) { List<File> files = new ArrayList<>(); walkin(new File(dir), files); for (File file : files) { try { FileInputStream stream = new FileInputStream(file); Buf...
java
public static void load(String dir, List<String[]> sentences, List<PennTreebankPOS[]> labels) { List<File> files = new ArrayList<>(); walkin(new File(dir), files); for (File file : files) { try { FileInputStream stream = new FileInputStream(file); Buf...
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Load training data from a corpora. @param dir a file object defining the top directory
[ "Load", "training", "data", "from", "a", "corpora", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/nlp/src/main/java/smile/nlp/pos/HMMPOSTagger.java#L344-L393
17,284
haifengl/smile
nlp/src/main/java/smile/nlp/pos/HMMPOSTagger.java
HMMPOSTagger.walkin
public static void walkin(File dir, List<File> files) { String pattern = ".POS"; File[] listFile = dir.listFiles(); if (listFile != null) { for (File file : listFile) { if (file.isDirectory()) { walkin(file, files); ...
java
public static void walkin(File dir, List<File> files) { String pattern = ".POS"; File[] listFile = dir.listFiles(); if (listFile != null) { for (File file : listFile) { if (file.isDirectory()) { walkin(file, files); ...
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Recursive function to descend into the directory tree and find all the files that end with ".POS" @param dir a file object defining the top directory
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/nlp/src/main/java/smile/nlp/pos/HMMPOSTagger.java#L400-L414
17,285
haifengl/smile
nlp/src/main/java/smile/nlp/pos/HMMPOSTagger.java
HMMPOSTagger.main
public static void main(String[] argvs) { List<String[]> sentences = new ArrayList<>(); List<PennTreebankPOS[]> labels = new ArrayList<>(); load("D:\\sourceforge\\corpora\\PennTreebank\\PennTreebank2\\TAGGED\\POS\\WSJ", sentences, labels); load("D:\\sourceforge\\corpora\...
java
public static void main(String[] argvs) { List<String[]> sentences = new ArrayList<>(); List<PennTreebankPOS[]> labels = new ArrayList<>(); load("D:\\sourceforge\\corpora\\PennTreebank\\PennTreebank2\\TAGGED\\POS\\WSJ", sentences, labels); load("D:\\sourceforge\\corpora\...
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Train the default model on WSJ and BROWN datasets.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/nlp/src/main/java/smile/nlp/pos/HMMPOSTagger.java#L419-L440
17,286
haifengl/smile
math/src/main/java/smile/sort/QuickSort.java
QuickSort.sort
public static <T extends Comparable<? super T>> int[] sort(T[] arr) { int[] order = new int[arr.length]; for (int i = 0; i < order.length; i++) { order[i] = i; } sort(arr, order); return order; }
java
public static <T extends Comparable<? super T>> int[] sort(T[] arr) { int[] order = new int[arr.length]; for (int i = 0; i < order.length; i++) { order[i] = i; } sort(arr, order); return order; }
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Sorts the specified array into ascending order. @return the original index of elements after sorting in range [0, n).
[ "Sorts", "the", "specified", "array", "into", "ascending", "order", "." ]
e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/math/src/main/java/smile/sort/QuickSort.java#L886-L893
17,287
haifengl/smile
math/src/main/java/smile/sort/QuickSort.java
QuickSort.sort
public static <T extends Comparable<? super T>> void sort(T[] arr, int[] brr) { sort(arr, brr, arr.length); }
java
public static <T extends Comparable<? super T>> void sort(T[] arr, int[] brr) { sort(arr, brr, arr.length); }
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Besides sorting the array arr, the array brr will be also rearranged as the same order of arr.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/math/src/main/java/smile/sort/QuickSort.java#L899-L901
17,288
haifengl/smile
data/src/main/java/smile/data/SparseDataset.java
SparseDataset.set
public void set(int i, int y) { if (response == null) { throw new IllegalArgumentException("The dataset has no response values."); } if (response.getType() != Attribute.Type.NOMINAL) { throw new IllegalArgumentException("The response variable is not n...
java
public void set(int i, int y) { if (response == null) { throw new IllegalArgumentException("The dataset has no response values."); } if (response.getType() != Attribute.Type.NOMINAL) { throw new IllegalArgumentException("The response variable is not n...
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Set the class label of a datum. If the index exceeds the current matrix size, the matrix will resize itself. @param i the row index of entry. @param y the class label or real-valued response of the datum.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/data/src/main/java/smile/data/SparseDataset.java#L190-L211
17,289
haifengl/smile
data/src/main/java/smile/data/SparseDataset.java
SparseDataset.set
public void set(int i, double y, double weight) { if (i < 0) { throw new IllegalArgumentException("Invalid index: i = " + i); } int nrows = size(); if (i >= nrows) { for (int k = nrows; k <= i; k++) { data.add(new Datum<>(new SparseArray())); ...
java
public void set(int i, double y, double weight) { if (i < 0) { throw new IllegalArgumentException("Invalid index: i = " + i); } int nrows = size(); if (i >= nrows) { for (int k = nrows; k <= i; k++) { data.add(new Datum<>(new SparseArray())); ...
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Set the class label of real-valued response of a datum. If the index exceeds the current matrix size, the matrix will resize itself. @param i the row index of entry. @param y the class label or real-valued response of the datum. @param weight the optional weight of the datum.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/data/src/main/java/smile/data/SparseDataset.java#L249-L264
17,290
haifengl/smile
data/src/main/java/smile/data/SparseDataset.java
SparseDataset.set
public void set(int i, int j, double x) { if (i < 0 || j < 0) { throw new IllegalArgumentException("Invalid index: i = " + i + " j = " + j); } int nrows = size(); if (i >= nrows) { for (int k = nrows; k <= i; k++) { data.add(new Datum<>(new Sparse...
java
public void set(int i, int j, double x) { if (i < 0 || j < 0) { throw new IllegalArgumentException("Invalid index: i = " + i + " j = " + j); } int nrows = size(); if (i >= nrows) { for (int k = nrows; k <= i; k++) { data.add(new Datum<>(new Sparse...
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Set a nonzero entry into the matrix. If the index exceeds the current matrix size, the matrix will resize itself. @param i the row index of entry. @param j the column index of entry. @param x the value of entry.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/data/src/main/java/smile/data/SparseDataset.java#L273-L298
17,291
haifengl/smile
data/src/main/java/smile/data/SparseDataset.java
SparseDataset.remove
public Datum<SparseArray> remove(int i) { Datum<SparseArray> datum = data.remove(i); n -= datum.x.size(); for (SparseArray.Entry item : datum.x) { colSize[item.i]--; } return datum; }
java
public Datum<SparseArray> remove(int i) { Datum<SparseArray> datum = data.remove(i); n -= datum.x.size(); for (SparseArray.Entry item : datum.x) { colSize[item.i]--; } return datum; }
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Removes the element at the specified position in this dataset. @param i the index of the element to be removed. @return the element previously at the specified position.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/data/src/main/java/smile/data/SparseDataset.java#L332-L341
17,292
haifengl/smile
data/src/main/java/smile/data/SparseDataset.java
SparseDataset.unitize
public void unitize() { for (Datum<SparseArray> row : this) { double sum = 0.0; for (SparseArray.Entry e : row.x) { sum += Math.sqr(e.x); } sum = Math.sqrt(sum); for (SparseArray.Entry e : row.x) { e.x /= sum; ...
java
public void unitize() { for (Datum<SparseArray> row : this) { double sum = 0.0; for (SparseArray.Entry e : row.x) { sum += Math.sqr(e.x); } sum = Math.sqrt(sum); for (SparseArray.Entry e : row.x) { e.x /= sum; ...
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Unitize each row so that L2 norm of x = 1.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/data/src/main/java/smile/data/SparseDataset.java#L346-L360
17,293
haifengl/smile
data/src/main/java/smile/data/SparseDataset.java
SparseDataset.unitize1
public void unitize1() { for (Datum<SparseArray> row : this) { double sum = 0.0; for (SparseArray.Entry e : row.x) { sum += Math.abs(e.x); } for (SparseArray.Entry e : row.x) { e.x /= sum; } } }
java
public void unitize1() { for (Datum<SparseArray> row : this) { double sum = 0.0; for (SparseArray.Entry e : row.x) { sum += Math.abs(e.x); } for (SparseArray.Entry e : row.x) { e.x /= sum; } } }
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Unitize each row so that L1 norm of x is 1.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/data/src/main/java/smile/data/SparseDataset.java#L365-L377
17,294
haifengl/smile
data/src/main/java/smile/data/SparseDataset.java
SparseDataset.iterator
@Override public Iterator<Datum<SparseArray>> iterator() { return new Iterator<Datum<SparseArray>>() { /** * Current position. */ int i = 0; @Override public boolean hasNext() { return i < data.size(); } ...
java
@Override public Iterator<Datum<SparseArray>> iterator() { return new Iterator<Datum<SparseArray>>() { /** * Current position. */ int i = 0; @Override public boolean hasNext() { return i < data.size(); } ...
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Returns an iterator over the elements in this dataset in proper sequence. @return an iterator over the elements in this dataset in proper sequence
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/data/src/main/java/smile/data/SparseDataset.java#L411-L435
17,295
haifengl/smile
data/src/main/java/smile/data/SparseDataset.java
SparseDataset.toArray
public double[][] toArray() { int m = data.size(); double[][] a = new double[m][ncols()]; for (int i = 0; i < m; i++) { for (SparseArray.Entry item : get(i).x) { a[i][item.i] = item.x; } } return a; }
java
public double[][] toArray() { int m = data.size(); double[][] a = new double[m][ncols()]; for (int i = 0; i < m; i++) { for (SparseArray.Entry item : get(i).x) { a[i][item.i] = item.x; } } return a; }
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Returns a dense two-dimensional array containing the whole matrix in this dataset in proper sequence. @return a dense two-dimensional array containing the whole matrix in this dataset in proper sequence.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/data/src/main/java/smile/data/SparseDataset.java#L444-L455
17,296
haifengl/smile
core/src/main/java/smile/neighbor/MPLSH.java
MPLSH.put
public void put(double[] key, E value) { int index = keys.size(); keys.add(key); data.add(value); for (Hash h : hash) { h.add(index, key, value); } }
java
public void put(double[] key, E value) { int index = keys.size(); keys.add(key); data.add(value); for (Hash h : hash) { h.add(index, key, value); } }
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Insert an item into the hash table.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/neighbor/MPLSH.java#L833-L840
17,297
haifengl/smile
core/src/main/java/smile/neighbor/MPLSH.java
MPLSH.nearest
public Neighbor<double[], E> nearest(double[] q, double recall, int T) { if (recall > 1 || recall < 0) { throw new IllegalArgumentException("Invalid recall: " + recall); } double alpha = 1 - Math.pow(1 - recall, 1.0 / hash.size()); IntArrayList candidates = new IntArrayList...
java
public Neighbor<double[], E> nearest(double[] q, double recall, int T) { if (recall > 1 || recall < 0) { throw new IllegalArgumentException("Invalid recall: " + recall); } double alpha = 1 - Math.pow(1 - recall, 1.0 / hash.size()); IntArrayList candidates = new IntArrayList...
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Returns the approximate nearest neighbor. A posteriori multiple probe model has to be trained already. @param q the query object. @param recall the expected recall rate. @param T the maximum number of probes.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/core/src/main/java/smile/neighbor/MPLSH.java#L900-L949
17,298
haifengl/smile
math/src/main/java/smile/sort/HeapSelect.java
HeapSelect.sort
public void sort() { if (!sorted) { sort(heap, Math.min(k,n)); sorted = true; } }
java
public void sort() { if (!sorted) { sort(heap, Math.min(k,n)); sorted = true; } }
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Sort the smallest values.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/math/src/main/java/smile/sort/HeapSelect.java#L122-L127
17,299
haifengl/smile
plot/src/main/java/smile/swing/Printer.java
Printer.print
public void print(Printable painter) { printer.setPrintable(painter); if (printer.printDialog(printAttributes)) { try { printer.print(printAttributes); } catch (PrinterException ex) { logger.error("Failed to print", ex); JOptionPane...
java
public void print(Printable painter) { printer.setPrintable(painter); if (printer.printDialog(printAttributes)) { try { printer.print(printAttributes); } catch (PrinterException ex) { logger.error("Failed to print", ex); JOptionPane...
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Prints a document that implements Printable interface. @param painter the Printable that renders each page of the document.
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e27e43e90fbaacce3f99d30120cf9dd6a764c33d
https://github.com/haifengl/smile/blob/e27e43e90fbaacce3f99d30120cf9dd6a764c33d/plot/src/main/java/smile/swing/Printer.java#L74-L84