protected MaximizableACRF (InstanceList ilist) { logger.finest ("Initializing MaximizableACRF."); /* allocate for weights, constraints and expectations */ this.trainData = ilist; initWeights(trainData); initConstraintsExpectations(); int numInstances = trainData.size(); cachedGradient = new double[numParameters]; cachedValueStale = cachedGradientStale = true; /* if (cacheUnrolledGraphs) { unrolledGraphs = new UnrolledGraph [numInstances]; } */ logger.info("Number of training instances = " + numInstances ); logger.info("Number of parameters = " + numParameters ); logger.info("Default feature index = " + defaultFeatureIndex ); describePrior(); logger.fine("Computing constraints"); collectConstraints (trainData); }
protected MaximizableACRF (InstanceList ilist) { logger.finest ("Initializing MaximizableACRF."); /* allocate for weights, constraints and expectations */ this.trainData = ilist; initWeights(trainData); initConstraintsExpectations(); int numInstances = trainData.size(); cachedGradient = new double[numParameters]; cachedValueStale = cachedGradientStale = true; /* if (cacheUnrolledGraphs) { unrolledGraphs = new UnrolledGraph [numInstances]; } */ logger.info("Number of training instances = " + numInstances ); logger.info("Number of parameters = " + numParameters ); logger.info("Default feature index = " + defaultFeatureIndex ); describePrior(); logger.fine("Computing constraints"); collectConstraints (trainData); }
protected MaximizableACRF (InstanceList ilist) { logger.finest ("Initializing MaximizableACRF."); /* allocate for weights, constraints and expectations */ this.trainData = ilist; initWeights(trainData); initConstraintsExpectations(); int numInstances = trainData.size(); cachedGradient = new double[numParameters]; cachedValueStale = cachedGradientStale = true; /* if (cacheUnrolledGraphs) { unrolledGraphs = new UnrolledGraph [numInstances]; } */ logger.info("Number of training instances = " + numInstances ); logger.info("Number of parameters = " + numParameters ); logger.info("Default feature index = " + defaultFeatureIndex ); describePrior(); logger.fine("Computing constraints"); collectConstraints (trainData); }