public Optimizer getOptimizer (InstanceList trainingSet) { getOptimizableCRF(trainingSet); // this will set this.mcrf if necessary if (opt == null || ocrf != opt.getOptimizable()) opt = new LimitedMemoryBFGS(ocrf); // Alternative: opt = new ConjugateGradient (0.001); return opt; }
public static void main (String[] args) throws Exception { InstanceList data = InstanceList.load(new File(args[0])); LinearRegressionTrainer trainer = new LinearRegressionTrainer(data); Optimizer optimizer = new OrthantWiseLimitedMemoryBFGS(trainer); //Optimizer optimizer = new LimitedMemoryBFGS(trainer); optimizer.optimize(); optimizer.optimize(); }
public static void main (String[] args) throws Exception { InstanceList data = InstanceList.load(new File(args[0])); LinearRegressionTrainer trainer = new LinearRegressionTrainer(data); Optimizer optimizer = new OrthantWiseLimitedMemoryBFGS(trainer); //Optimizer optimizer = new LimitedMemoryBFGS(trainer); optimizer.optimize(); optimizer.optimize(); }
protected void preamble (ClassifierTrainer ct) { if (ct instanceof ClassifierTrainer.ByOptimization) { Optimizable opt; int iteration = ((ClassifierTrainer.ByOptimization)ct).getIteration(); if ((opt = ((ClassifierTrainer.ByOptimization)ct).getOptimizer().getOptimizable()) instanceof Optimizable.ByValue) logger.info ("Evaluator iteration="+iteration+" cost="+((Optimizable.ByValue)opt).getValue()); else logger.info ("Evaluator iteration="+iteration+" cost=NA (not Optimizable.ByValue)"); } }
public static void main (String[] args) throws Exception { InstanceList data = InstanceList.load(new File(args[0])); LinearRegressionTrainer trainer = new LinearRegressionTrainer(data); Optimizer optimizer = new OrthantWiseLimitedMemoryBFGS(trainer); //Optimizer optimizer = new LimitedMemoryBFGS(trainer); optimizer.optimize(); optimizer.optimize(); }
protected void preamble (TransducerTrainer tt) { int iteration = tt.getIteration(); Optimizable opt; if (tt instanceof TransducerTrainer.ByOptimization && (opt = ((TransducerTrainer.ByOptimization)tt).getOptimizer().getOptimizable()) instanceof Optimizable.ByValue) logger.info ("Evaluator iteration="+iteration+" cost="+((Optimizable.ByValue)opt).getValue()); else logger.info ("Evaluator iteration="+iteration+" cost=NA (not Optimizable.ByValue)"); }
public void testOrthantWiseLBFGSWithoutL1() { SimplePoly poly = new SimplePoly(); Optimizer bfgs = new OrthantWiseLimitedMemoryBFGS(poly); bfgs.optimize(); assertEquals(5.0 / 6.0, poly.params[0], 1e-3); }
public Optimizer getOptimizer (InstanceList trainingSet) { getOptimizableCRF(trainingSet); if (optimizer == null || optimizable != optimizer.getOptimizable()) { optimizer = new LimitedMemoryBFGS(threadedOptimizable); } return optimizer; }
public void testConjugateGradient() { SimplePoly poly = new SimplePoly(); Optimizer cg = new ConjugateGradient(poly); cg.optimize(); assertEquals(5.0 / 6.0, poly.params[0], 1e-3); }
protected void preamble (ClassifierTrainer ct) { if (ct instanceof ClassifierTrainer.ByOptimization) { Optimizable opt; int iteration = ((ClassifierTrainer.ByOptimization)ct).getIteration(); if ((opt = ((ClassifierTrainer.ByOptimization)ct).getOptimizer().getOptimizable()) instanceof Optimizable.ByValue) logger.info ("Evaluator iteration="+iteration+" cost="+((Optimizable.ByValue)opt).getValue()); else logger.info ("Evaluator iteration="+iteration+" cost=NA (not Optimizable.ByValue)"); } }
for (int i = 0; i < numIterations; i++) { try { converged = opt.optimize (1); iterationCount++; logger.info ("CRF finished one iteration of maximizer, i="+i);
protected void preamble (TransducerTrainer tt) { int iteration = tt.getIteration(); Optimizable opt; if (tt instanceof TransducerTrainer.ByOptimization && (opt = ((TransducerTrainer.ByOptimization)tt).getOptimizer().getOptimizable()) instanceof Optimizable.ByValue) logger.info ("Evaluator iteration="+iteration+" cost="+((Optimizable.ByValue)opt).getValue()); else logger.info ("Evaluator iteration="+iteration+" cost=NA (not Optimizable.ByValue)"); }
for (int i = 0; i < numIterations; i++) { try { converged = opt.optimize (1); iterationCount++; logger.info ("CRF finished one iteration of maximizer, i="+i);
public Optimizer getOptimizer (InstanceList trainingSet) { getOptimizableCRF(trainingSet); if (optimizer == null || optimizable != optimizer.getOptimizable()) { optimizer = new LimitedMemoryBFGS(threadedOptimizable); } return optimizer; }
for (int i = 0; i < numIterations; i++) { try { converged = optimizer.optimize (1); iterationCount++; logger.info ("CRF finished one iteration of maximizer, i="+i);
public Optimizer getOptimizer(InstanceList trainingSet) { getOptimizableCRF(trainingSet); // this will set this.mcrf if necessary if (opt == null || ocrf != opt.getOptimizable()) { opt = new LimitedMemoryBFGS(ocrf); // Alternative: opt = new ConjugateGradient (0.001); } return opt; }
for (int i = 0; i < numIterations; i++) { try { converged = optimizer.optimize (1); iterationCount++; logger.info ("CRF finished one iteration of maximizer, i="+i);
public Optimizer getOptimizer (InstanceList trainingSet) { getOptimizableCRF(trainingSet); // this will set this.mcrf if necessary if (opt == null || ocrf != opt.getOptimizable()) opt = new LimitedMemoryBFGS(ocrf); // Alternative: opt = new ConjugateGradient (0.001); return opt; }
public Optimizer getOptimizer(InstanceList trainingSet) { getOptimizableCRF(trainingSet); if (opt == null || ocrf != opt.getOptimizable()) opt = new OrthantWiseLimitedMemoryBFGS(ocrf, l1Weight); return opt; }