@Override public double[] initial() { return initial(rand); } public double[] initial(boolean useRandomSeed) {
public double[] initial(boolean useRandomSeed) { Random randToUse = useRandomSeed ? new Random() : rand; return initial(randToUse); }
initialWeights = func.initial(); } else { try {
int[][][][] partialData = createPartialDataForLOP(lopIter, data); if (flags.randomLopWeights) { lopExpertWeights[lopIter] = super.getObjectiveFunction(partialData, labels).initial(); } else { lopExpertWeights[lopIter] = super.trainWeights(partialData, labels, evaluators, pruneFeatureItr, null); System.arraycopy(lopExpertWeights, 0, newLopExpertWeights, 0, lopExpertWeights.length); if (flags.randomLopWeights) { newLopExpertWeights[numLopExpert] = super.getObjectiveFunction(data, labels).initial(); } else { newLopExpertWeights[numLopExpert] = super.trainWeights(data, labels, evaluators, pruneFeatureItr, null);
@Override public double[] initial() { return initial(rand); } public double[] initial(boolean useRandomSeed) {
@Override public double[] initial() { return initial(rand); } public double[] initial(boolean useRandomSeed) {
public double[] initial(boolean useRandomSeed) { Random randToUse = useRandomSeed ? new Random() : rand; return initial(rand); }
public double[] initial(boolean useRandomSeed) { Random randToUse = useRandomSeed ? new Random() : rand; return initial(randToUse); }
initialWeights = func.initial(); } else { try {
int[][][][] partialData = createPartialDataForLOP(lopIter, data); if (flags.randomLopWeights) { lopExpertWeights[lopIter] = super.getObjectiveFunction(partialData, labels).initial(); } else { lopExpertWeights[lopIter] = super.trainWeights(partialData, labels, evaluators, pruneFeatureItr, null); System.arraycopy(lopExpertWeights, 0, newLopExpertWeights, 0, lopExpertWeights.length); if (flags.randomLopWeights) { newLopExpertWeights[numLopExpert] = super.getObjectiveFunction(data, labels).initial(); } else { newLopExpertWeights[numLopExpert] = super.trainWeights(data, labels, evaluators, pruneFeatureItr, null);
initialWeights = func.initial(); } else { try {
int[][][][] partialData = createPartialDataForLOP(lopIter, data); if (flags.randomLopWeights) { lopExpertWeights[lopIter] = super.getObjectiveFunction(partialData, labels).initial(); } else { lopExpertWeights[lopIter] = super.trainWeights(partialData, labels, evaluators, pruneFeatureItr, null); System.arraycopy(lopExpertWeights, 0, newLopExpertWeights, 0, lopExpertWeights.length); if (flags.randomLopWeights) { newLopExpertWeights[numLopExpert] = super.getObjectiveFunction(data, labels).initial(); } else { newLopExpertWeights[numLopExpert] = super.trainWeights(data, labels, evaluators, pruneFeatureItr, null);
initialWeights = func.initial(); } else { try {