本文整理汇总了Java中cc.mallet.optimize.tests.TestOptimizable类的典型用法代码示例。如果您正苦于以下问题：Java TestOptimizable类的具体用法？Java TestOptimizable怎么用？Java TestOptimizable使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
TestOptimizable类属于cc.mallet.optimize.tests包，在下文中一共展示了TestOptimizable类的7个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于我们的系统推荐出更棒的Java代码示例。
示例1: testGetSetParameters
import cc.mallet.optimize.tests.TestOptimizable; //导入依赖的package包/类
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);
}
开发者ID:kostagiolasn，项目名称:NucleosomePatternClassifier，代码行数:18，代码来源:TestCRF.java
示例2: testGetSetParameters
import cc.mallet.optimize.tests.TestOptimizable; //导入依赖的package包/类
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);
}
开发者ID:kostagiolasn，项目名称:NucleosomePatternClassifier，代码行数:18，代码来源:TestMEMM.java
示例3: testSpaceMaximizable
import cc.mallet.optimize.tests.TestOptimizable; //导入依赖的package包/类
public void testSpaceMaximizable ()
{
Pipe p = makeSpacePredictionPipe ();
InstanceList training = new InstanceList (p);
// String[] data = { TestMEMM.data[0], }; // TestMEMM.data[1], TestMEMM.data[2], TestMEMM.data[3], };
// String[] data = { "ab" };
training.addThruPipe (new ArrayIterator (data));
// CRF4 memm = new CRF4 (p, null);
MEMM memm = new MEMM (p, null);
memm.addFullyConnectedStatesForLabels ();
memm.addStartState();
memm.setWeightsDimensionAsIn(training);
MEMMTrainer memmt = new MEMMTrainer (memm);
// memm.gatherTrainingSets (training); // ANNOYING: Need to set up per-instance training sets
memmt.train (training, 1); // Set weights dimension, gathers training sets, etc.
// memm.print();
// memm.printGradient = true;
// memm.printInstanceLists();
// memm.setGaussianPriorVariance (Double.POSITIVE_INFINITY);
Optimizable.ByGradientValue mcrf = memmt.getOptimizableMEMM(training);
TestOptimizable.setNumComponents (150);
TestOptimizable.testValueAndGradient (mcrf);
}
开发者ID:kostagiolasn，项目名称:NucleosomePatternClassifier，代码行数:28，代码来源:TestMEMM.java
示例4: testSetGetParameters
import cc.mallet.optimize.tests.TestOptimizable; //导入依赖的package包/类
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);
}
开发者ID:kostagiolasn，项目名称:NucleosomePatternClassifier，代码行数:10，代码来源:TestMaxEntTrainer.java
示例5: testRandomMaximizable
import cc.mallet.optimize.tests.TestOptimizable; //导入依赖的package包/类
public void testRandomMaximizable ()
{
MaxEntTrainer trainer = new MaxEntTrainer();
Alphabet fd = dictOfSize (6);
String[] classNames = new String[] {"class0", "class1"};
InstanceList ilist = new InstanceList (new Randoms(1), fd, classNames, 20);
Optimizable.ByGradientValue maxable = trainer.getOptimizable (ilist);
TestOptimizable.testValueAndGradient (maxable);
}
开发者ID:kostagiolasn，项目名称:NucleosomePatternClassifier，代码行数:10，代码来源:TestMaxEntTrainer.java
示例6: testTrainedMaximizable
import cc.mallet.optimize.tests.TestOptimizable; //导入依赖的package包/类
public void testTrainedMaximizable ()
{
MaxEntTrainer trainer = new MaxEntTrainer();
Alphabet fd = dictOfSize (6);
String[] classNames = new String[] {"class0", "class1"};
InstanceList ilist = new InstanceList (new Randoms(1), fd, classNames, 20);
MaxEnt me = (MaxEnt)trainer.train(ilist);
Optimizable.ByGradientValue maxable = trainer.getOptimizable (ilist, me);
TestOptimizable.testValueAndGradientCurrentParameters (maxable);
}
开发者ID:kostagiolasn，项目名称:NucleosomePatternClassifier，代码行数:11，代码来源:TestMaxEntTrainer.java
示例7: ignoretestSpaceMaximizable
import cc.mallet.optimize.tests.TestOptimizable; //导入依赖的package包/类
public void ignoretestSpaceMaximizable ()
{
Pipe p = makeSpacePredictionPipe ();
InstanceList training = new InstanceList (p);
// String[] data = { TestMEMM.data[0], }; // TestMEMM.data[1], TestMEMM.data[2], TestMEMM.data[3], };
// String[] data = { "ab" };
training.addThruPipe (new ArrayIterator (data));
// CRF4 memm = new CRF4 (p, null);
MEMM memm = new MEMM (p, null);
memm.addFullyConnectedStatesForLabels ();
memm.addStartState();
memm.setWeightsDimensionAsIn(training);
MEMMTrainer memmt = new MEMMTrainer (memm);
// memm.gatherTrainingSets (training); // ANNOYING: Need to set up per-instance training sets
memmt.train (training, 1); // Set weights dimension, gathers training sets, etc.
// memm.print();
// memm.printGradient = true;
// memm.printInstanceLists();
// memm.setGaussianPriorVariance (Double.POSITIVE_INFINITY);
Optimizable.ByGradientValue mcrf = memmt.getOptimizableMEMM(training);
TestOptimizable.setNumComponents (150);
TestOptimizable.testValueAndGradient (mcrf);
}
开发者ID:cmoen，项目名称:mallet，代码行数:28，代码来源:TestMEMM.java
注：本文中的cc.mallet.optimize.tests.TestOptimizable类示例整理自Github/MSDocs等源码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。 |
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