protected CliquePotentialFunction getCliquePotentialFunctionForTest() { if (cliquePotentialFunction == null) { cliquePotentialFunction = new LinearCliquePotentialFunction(weights); } return cliquePotentialFunction; }
public void setWeights(double[][] weights) { this.weights = weights; cliquePotentialFunc = new LinearCliquePotentialFunction(weights); }
@Override public CliquePotentialFunction getCliquePotentialFunction(double[] x) { to2D(x, weights); return new LinearCliquePotentialFunction(weights); }
public CliquePotentialFunction getCliquePotentialFunction(double[] x) { double[] rawScales = separateLopScales(x); double[] scales = ArrayMath.softmax(rawScales); double[][][] learnedLopExpertWeights2D = lopExpertWeights2D; if (backpropTraining) { learnedLopExpertWeights2D = separateLopExpertWeights2D(x); } double[][] combinedWeights2D = combineAndScaleLopWeights2D(numLopExpert, learnedLopExpertWeights2D, scales); return new LinearCliquePotentialFunction(combinedWeights2D); }
CliquePotentialFunction cliquePotentialFunc = new LinearCliquePotentialFunction(combinedWeights2D); CRFCliqueTree<String> cliqueTree = CRFCliqueTree.getCalibratedCliqueTree(docData, labelIndices, numClasses, classIndex, backgroundSymbol, cliquePotentialFunc, null);
protected CliquePotentialFunction getCliquePotentialFunctionForTest() { if (cliquePotentialFunction == null) { cliquePotentialFunction = new LinearCliquePotentialFunction(weights); } return cliquePotentialFunction; }
public void setWeights(double[][] weights) { this.weights = weights; cliquePotentialFunc = new LinearCliquePotentialFunction(weights); }
protected CliquePotentialFunction getCliquePotentialFunctionForTest() { if (cliquePotentialFunction == null) { cliquePotentialFunction = new LinearCliquePotentialFunction(weights); } return cliquePotentialFunction; }
public void setWeights(double[][] weights) { this.weights = weights; cliquePotentialFunc = new LinearCliquePotentialFunction(weights); }
@Override public CliquePotentialFunction getCliquePotentialFunction(double[] x) { to2D(x, weights); return new LinearCliquePotentialFunction(weights); }
@Override public CliquePotentialFunction getCliquePotentialFunction(double[] x) { to2D(x, weights); return new LinearCliquePotentialFunction(weights); }
public CliquePotentialFunction getCliquePotentialFunction(double[] x) { double[] rawScales = separateLopScales(x); double[] scales = ArrayMath.softmax(rawScales); double[][][] learnedLopExpertWeights2D = lopExpertWeights2D; if (backpropTraining) { learnedLopExpertWeights2D = separateLopExpertWeights2D(x); } double[][] combinedWeights2D = combineAndScaleLopWeights2D(numLopExpert, learnedLopExpertWeights2D, scales); return new LinearCliquePotentialFunction(combinedWeights2D); }
public CliquePotentialFunction getCliquePotentialFunction(double[] x) { double[] rawScales = separateLopScales(x); double[] scales = ArrayMath.softmax(rawScales); double[][][] learnedLopExpertWeights2D = lopExpertWeights2D; if (backpropTraining) { learnedLopExpertWeights2D = separateLopExpertWeights2D(x); } double[][] combinedWeights2D = combineAndScaleLopWeights2D(numLopExpert, learnedLopExpertWeights2D, scales); return new LinearCliquePotentialFunction(combinedWeights2D); }
CliquePotentialFunction cliquePotentialFunc = new LinearCliquePotentialFunction(combinedWeights2D); CRFCliqueTree cliqueTree = CRFCliqueTree.getCalibratedCliqueTree(docData, labelIndices, numClasses, classIndex, backgroundSymbol, cliquePotentialFunc, null);
CliquePotentialFunction cliquePotentialFunc = new LinearCliquePotentialFunction(combinedWeights2D); CRFCliqueTree<String> cliqueTree = CRFCliqueTree.getCalibratedCliqueTree(docData, labelIndices, numClasses, classIndex, backgroundSymbol, cliquePotentialFunc, null);