public boolean train (ACRF acrf, InstanceList trainingList, InstanceList validationList, InstanceList testSet, ACRFEvaluator eval, int numIter) { Optimizable.ByGradientValue macrf = createOptimizable (acrf, trainingList); return train (acrf, trainingList, validationList, testSet, eval, numIter, macrf); }
public boolean train (ACRF acrf, InstanceList trainingList, InstanceList validationList, InstanceList testSet, ACRFEvaluator eval, int numIter) { Optimizable.ByGradientValue macrf = createOptimizable (acrf, trainingList); return train (acrf, trainingList, validationList, testSet, eval, numIter, macrf); }
public boolean train (ACRF acrf, InstanceList trainingList, InstanceList validationList, InstanceList testSet, ACRFEvaluator eval, int numIter) { Optimizable.ByGradientValue macrf = createOptimizable (acrf, trainingList); return train (acrf, trainingList, validationList, testSet, eval, numIter, macrf); }
public boolean incrementalTrain (ACRF acrf, InstanceList training, InstanceList validation, InstanceList testing, ACRFEvaluator eval, int numIter) { long stime = new Date ().getTime (); for (int i = 0; i < SIZE.length; i++) { InstanceList subset = training.split (new double[] {SIZE[i], 1 - SIZE[i]})[0]; logger.info ("Training on subset of size " + subset.size ()); Optimizable.ByGradientValue subset_macrf = createOptimizable (acrf, subset); train (acrf, training, validation, null, eval, SUBSET_ITER, subset_macrf); logger.info ("Subset training " + i + " finished..."); } long etime = new Date ().getTime (); logger.info ("All subset training finished. Time = " + (etime - stime) + " ms."); return train (acrf, training, validation, testing, eval, numIter); }
public boolean incrementalTrain (ACRF acrf, InstanceList training, InstanceList validation, InstanceList testing, ACRFEvaluator eval, int numIter) { long stime = new Date ().getTime (); for (int i = 0; i < SIZE.length; i++) { InstanceList subset = training.split (new double[] {SIZE[i], 1 - SIZE[i]})[0]; logger.info ("Training on subset of size " + subset.size ()); Optimizable.ByGradientValue subset_macrf = createOptimizable (acrf, subset); train (acrf, training, validation, null, eval, SUBSET_ITER, subset_macrf); logger.info ("Subset training " + i + " finished..."); } long etime = new Date ().getTime (); logger.info ("All subset training finished. Time = " + (etime - stime) + " ms."); return train (acrf, training, validation, testing, eval, numIter); }
public boolean incrementalTrain (ACRF acrf, InstanceList training, InstanceList validation, InstanceList testing, ACRFEvaluator eval, int numIter) { long stime = new Date ().getTime (); for (int i = 0; i < SIZE.length; i++) { InstanceList subset = training.split (new double[] {SIZE[i], 1 - SIZE[i]})[0]; logger.info ("Training on subset of size " + subset.size ()); Optimizable.ByGradientValue subset_macrf = createOptimizable (acrf, subset); train (acrf, training, validation, null, eval, SUBSET_ITER, subset_macrf); logger.info ("Subset training " + i + " finished..."); } long etime = new Date ().getTime (); logger.info ("All subset training finished. Time = " + (etime - stime) + " ms."); return train (acrf, training, validation, testing, eval, numIter); }
public boolean someUnsupportedTrain (ACRF acrf, InstanceList trainingList, InstanceList validationList, InstanceList testSet, ACRFEvaluator eval, int numIter) { Optimizable.ByGradientValue macrf = createOptimizable (acrf, trainingList); train (acrf, trainingList, validationList, testSet, eval, 5, macrf); ACRF.Template[] tmpls = acrf.getTemplates (); for (int ti = 0; ti < tmpls.length; ti++) tmpls[ti].addSomeUnsupportedWeights (trainingList); logger.info ("Some unsupporetd weights initialized. Training..."); return train (acrf, trainingList, validationList, testSet, eval, numIter, macrf); }
public boolean someUnsupportedTrain (ACRF acrf, InstanceList trainingList, InstanceList validationList, InstanceList testSet, ACRFEvaluator eval, int numIter) { Optimizable.ByGradientValue macrf = createOptimizable (acrf, trainingList); train (acrf, trainingList, validationList, testSet, eval, 5, macrf); ACRF.Template[] tmpls = acrf.getTemplates (); for (int ti = 0; ti < tmpls.length; ti++) tmpls[ti].addSomeUnsupportedWeights (trainingList); logger.info ("Some unsupporetd weights initialized. Training..."); return train (acrf, trainingList, validationList, testSet, eval, numIter, macrf); }
public boolean someUnsupportedTrain (ACRF acrf, InstanceList trainingList, InstanceList validationList, InstanceList testSet, ACRFEvaluator eval, int numIter) { Optimizable.ByGradientValue macrf = createOptimizable (acrf, trainingList); train (acrf, trainingList, validationList, testSet, eval, 5, macrf); ACRF.Template[] tmpls = acrf.getTemplates (); for (int ti = 0; ti < tmpls.length; ti++) tmpls[ti].addSomeUnsupportedWeights (trainingList); logger.info ("Some unsupporetd weights initialized. Training..."); return train (acrf, trainingList, validationList, testSet, eval, numIter, macrf); }