public void testSetGetParameters () { MaxEntTrainer trainer = new MaxEntTrainer(); Alphabet fd = dictOfSize (6); String[] classNames = new String[] {"class0", "class1", "class2"}; InstanceList ilist = new InstanceList (new Randoms(1), fd, classNames, 20); Optimizable.ByGradientValue maxable = trainer.getOptimizable (ilist); TestOptimizable.testGetSetParameters (maxable); }
public void testSetGetParameters () { MaxEntTrainer trainer = new MaxEntTrainer(); Alphabet fd = dictOfSize (6); String[] classNames = new String[] {"class0", "class1", "class2"}; InstanceList ilist = new InstanceList (new Randoms(1), fd, classNames, 20); Optimizable.ByGradientValue maxable = trainer.getOptimizable (ilist); TestOptimizable.testGetSetParameters (maxable); }
public void testGetSetParameters() { int inputVocabSize = 100; int numStates = 5; Alphabet inputAlphabet = new Alphabet(); for (int i = 0; i < inputVocabSize; i++) inputAlphabet.lookupIndex("feature" + i); Alphabet outputAlphabet = new Alphabet(); MEMM memm = new MEMM (inputAlphabet, outputAlphabet); String[] stateNames = new String[numStates]; for (int i = 0; i < numStates; i++) stateNames[i] = "state" + i; memm.addFullyConnectedStates(stateNames); MEMMTrainer memmt = new MEMMTrainer (memm); MEMMTrainer.MEMMOptimizableByLabelLikelihood omemm = memmt.getOptimizableMEMM (new InstanceList(null)); TestOptimizable.testGetSetParameters(omemm); }
public void testGetSetParameters() { int inputVocabSize = 100; int numStates = 5; Alphabet inputAlphabet = new Alphabet(); for (int i = 0; i < inputVocabSize; i++) inputAlphabet.lookupIndex("feature" + i); Alphabet outputAlphabet = new Alphabet(); MEMM memm = new MEMM (inputAlphabet, outputAlphabet); String[] stateNames = new String[numStates]; for (int i = 0; i < numStates; i++) stateNames[i] = "state" + i; memm.addFullyConnectedStates(stateNames); MEMMTrainer memmt = new MEMMTrainer (memm); MEMMTrainer.MEMMOptimizableByLabelLikelihood omemm = memmt.getOptimizableMEMM (new InstanceList(null)); TestOptimizable.testGetSetParameters(omemm); }
public void testGetSetParameters() { int inputVocabSize = 100; int numStates = 5; Alphabet inputAlphabet = new Alphabet(); for (int i = 0; i < inputVocabSize; i++) inputAlphabet.lookupIndex("feature" + i); Alphabet outputAlphabet = new Alphabet(); CRF crf = new CRF(inputAlphabet, outputAlphabet); String[] stateNames = new String[numStates]; for (int i = 0; i < numStates; i++) stateNames[i] = "state" + i; crf.addFullyConnectedStates(stateNames); CRFTrainerByLabelLikelihood crft = new CRFTrainerByLabelLikelihood(crf); Optimizable.ByGradientValue mcrf = crft .getOptimizableCRF(new InstanceList(null)); TestOptimizable.testGetSetParameters(mcrf); }
public void testGetSetParameters() { int inputVocabSize = 100; int numStates = 5; Alphabet inputAlphabet = new Alphabet(); for (int i = 0; i < inputVocabSize; i++) inputAlphabet.lookupIndex("feature" + i); Alphabet outputAlphabet = new Alphabet(); CRF crf = new CRF(inputAlphabet, outputAlphabet); String[] stateNames = new String[numStates]; for (int i = 0; i < numStates; i++) stateNames[i] = "state" + i; crf.addFullyConnectedStates(stateNames); CRFTrainerByLabelLikelihood crft = new CRFTrainerByLabelLikelihood(crf); Optimizable.ByGradientValue mcrf = crft .getOptimizableCRF(new InstanceList(null)); TestOptimizable.testGetSetParameters(mcrf); }