本文整理汇总了Java中edu.stanford.nlp.sequences.SeqClassifierFlags类的典型用法代码示例。如果您正苦于以下问题：Java SeqClassifierFlags类的具体用法？Java SeqClassifierFlags怎么用？Java SeqClassifierFlags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。
SeqClassifierFlags类属于edu.stanford.nlp.sequences包，在下文中一共展示了SeqClassifierFlags类的20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: BisequenceEmpiricalNERPrior
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
public BisequenceEmpiricalNERPrior(String backgroundSymbol, Index<String> classIndex, Index<String> tagIndex, List<IN> doc, Pair<double[][], double[][]> matrices, SeqClassifierFlags flags) {
this.flags = flags;
this.classIndex = classIndex;
this.tagIndex = tagIndex;
this.backgroundSymbolIndex = classIndex.indexOf(backgroundSymbol);
this.numClasses = classIndex.size();
this.numTags = tagIndex.size();
this.possibleValues = new int[numClasses];
for (int i=0; i<numClasses; i++) {
possibleValues[i] = i;
}
this.wordDoc = new ArrayList<String>(doc.size());
for (IN w: doc) {
wordDoc.add(w.get(CoreAnnotations.TextAnnotation.class));
}
entityMatrix = matrices.first();
subEntityMatrix = matrices.second();
}
开发者ID:paulirwin，项目名称:Stanford.NER.Net，代码行数:19，代码来源:BisequenceEmpiricalNERPrior.java
示例2: loadClassifier
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
/** Load a classifier from the given Stream.
* <i>Implementation note: </i> This method <i>does not</i> close the
* Stream that it reads from.
*
* @param ois The ObjectInputStream to load the serialized classifier from
*
* @throws IOException If there are problems accessing the input stream
* @throws ClassCastException If there are problems interpreting the serialized data
* @throws ClassNotFoundException If there are problems interpreting the serialized data
* */
@SuppressWarnings("unchecked")
@Override
public void loadClassifier(ObjectInputStream ois, Properties props) throws ClassCastException, IOException, ClassNotFoundException {
classifier = (LinearClassifier<String, String>) ois.readObject();
flags = (SeqClassifierFlags) ois.readObject();
featureFactory = (FeatureFactory) ois.readObject();
if (props != null) {
flags.setProperties(props);
}
reinit();
classIndex = (Index<String>) ois.readObject();
answerArrays = (Set<List<String>>) ois.readObject();
knownLCWords = (Set<String>) ois.readObject();
}
开发者ID:paulirwin，项目名称:Stanford.NER.Net，代码行数:29，代码来源:CMMClassifier.java
示例3: main
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
public static void main(String[] args) {
String path = IntelConfig.DEPARTMENT_TRAIN_PROPERTY;
Properties props = StringUtils.propFileToProperties(path);
SeqClassifierFlags flags = new SeqClassifierFlags(props);
CRFClassifier<CoreLabel> crf = new CRFClassifier<CoreLabel>(flags);
crf.train();
String modelPath = props.getProperty("serializeTo");
crf.serializeClassifier(modelPath);
System.out.println("Build model to " + modelPath);
}
开发者ID:intel-analytics，项目名称:InformationExtraction，代码行数:12，代码来源:TrainNerModel.java
示例4: loadClassifier
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
public static CRFClassifier<CoreLabel> loadClassifier(String options) throws IllegalArgumentException {
String[] inputFlags = options.split(" ");
Properties props = StringUtils.argsToProperties(inputFlags);
SeqClassifierFlags flags = new SeqClassifierFlags(props);
CRFClassifier<CoreLabel> crfSegmenter = new CRFClassifier<>(flags);
if(flags.loadClassifier == null) {
throw new IllegalArgumentException("missing -loadClassifier flag for CRF preprocessor.");
}
crfSegmenter.loadClassifierNoExceptions(flags.loadClassifier, props);
crfSegmenter.loadTagIndex();
return crfSegmenter;
}
开发者ID:stanfordnlp，项目名称:phrasal，代码行数:13，代码来源:CRFPreprocessor.java
示例5: CRFPostprocessor
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
public CRFPostprocessor(Properties props) {
// Currently, this class only supports one featureFactory.
props.put("featureFactory", CRFPostprocessorFeatureFactory.class.getName());
flags = new SeqClassifierFlags(props);
classifier = new CRFClassifier<CoreLabel>(flags);
}
开发者ID:stanfordnlp，项目名称:phrasal，代码行数:8，代码来源:CRFPostprocessor.java
示例6: train
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
public void train(ListMatrix<ListMatrix<MapMatrix<String, String>>> listMatrix) throws Exception {
List<List<CoreLabel>> sentenceList = new ArrayList<List<CoreLabel>>();
for (ListMatrix<MapMatrix<String, String>> innerList : listMatrix) {
List<CoreLabel> tokenList = new ArrayList<CoreLabel>();
sentenceList.add(tokenList);
for (MapMatrix<String, String> mapMatrix : innerList) {
CoreLabel l = new CoreLabel();
l.set(CoreAnnotations.TextAnnotation.class, mapMatrix.getAsString("Token"));
l.set(CoreAnnotations.AnswerAnnotation.class, mapMatrix.getAsString("Class"));
tokenList.add(l);
}
}
SeqClassifierFlags flags = new SeqClassifierFlags();
flags.maxLeft = 3;
flags.useClassFeature = true;
flags.useWord = true;
flags.maxNGramLeng = 6;
flags.usePrev = true;
flags.useNext = true;
flags.useDisjunctive = true;
flags.useSequences = true;
flags.usePrevSequences = true;
flags.useTypeSeqs = true;
flags.useTypeSeqs2 = true;
flags.useTypeySequences = true;
flags.wordShape = WordShapeClassifier.WORDSHAPECHRIS2;
flags.useNGrams = true;
crf = new CRFClassifier<CoreLabel>(flags);
crf.train(sentenceList, null);
}
开发者ID:jdmp，项目名称:java-data-mining-package，代码行数:33，代码来源:StanfordTagger.java
示例7: init
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
public void init(SeqClassifierFlags flags) {
super.init(flags);
initGazette();
if (flags.useDistSim) {
initLexicon(flags);
}
}
开发者ID:paulirwin，项目名称:Stanford.NER.Net，代码行数:8，代码来源:NERFeatureFactory.java
示例8: EmpiricalNERPriorBIO
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
public EmpiricalNERPriorBIO(String backgroundSymbol, Index<String> classIndex, Index<String> tagIndex, List<IN> doc, Pair<double[][], double[][]> matrices, SeqClassifierFlags flags) {
super(backgroundSymbol, classIndex, tagIndex, doc);
entityMatrix = matrices.first();
subEntityMatrix = matrices.second();
this.flags = flags;
ORGIndex = tagIndex.indexOf("ORG");
LOCIndex = tagIndex.indexOf("LOC");
}
开发者ID:paulirwin，项目名称:Stanford.NER.Net，代码行数:9，代码来源:EmpiricalNERPriorBIO.java
示例9: hiddenLayerOutput
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
public double[] hiddenLayerOutput(double[][] inputLayerWeights, int[] nodeCliqueFeatures, SeqClassifierFlags aFlag, double[] featureVal) {
int layerOneSize = inputLayerWeights.length;
if (layerOneCache == null || layerOneSize != layerOneCache.length)
layerOneCache = new double[layerOneSize];
for (int i = 0; i < layerOneSize; i++) {
double[] ws = inputLayerWeights[i];
double lOneW = 0;
double dotProd = 0;
for (int m = 0; m < nodeCliqueFeatures.length; m++) {
dotProd = ws[nodeCliqueFeatures[m]];
if (featureVal != null)
dotProd *= featureVal[m];
lOneW += dotProd;
}
layerOneCache[i] = lOneW;
}
if (!aFlag.useHiddenLayer)
return layerOneCache;
// transform layer one through hidden
if (hiddenLayerCache == null || layerOneSize != hiddenLayerCache.length)
hiddenLayerCache = new double[layerOneSize];
for (int i = 0; i < layerOneSize; i++) {
if (aFlag.useSigmoid) {
hiddenLayerCache[i] = sigmoid(layerOneCache[i]);
} else {
hiddenLayerCache[i] = Math.tanh(layerOneCache[i]);
}
}
return hiddenLayerCache;
}
开发者ID:paulirwin，项目名称:Stanford.NER.Net，代码行数:32，代码来源:NonLinearCliquePotentialFunction.java
示例10: CRFNonLinearLogConditionalObjectiveFunction
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
CRFNonLinearLogConditionalObjectiveFunction(int[][][][] data, int[][] labels, int window, Index<String> classIndex, List<Index<CRFLabel>> labelIndices, int[] map, SeqClassifierFlags flags, int numNodeFeatures, int numEdgeFeatures, double[][][][] featureVal) {
this.window = window;
this.classIndex = classIndex;
this.numClasses = classIndex.size();
this.labelIndices = labelIndices;
this.data = data;
this.featureVal = featureVal;
this.flags = flags;
this.map = map;
this.labels = labels;
this.prior = getPriorType(flags.priorType);
this.backgroundSymbol = flags.backgroundSymbol;
this.sigma = flags.sigma;
this.outputLayerSize = numClasses;
this.numHiddenUnits = flags.numHiddenUnits;
if (flags.arbitraryInputLayerSize != -1)
this.inputLayerSize = flags.arbitraryInputLayerSize;
else
this.inputLayerSize = numHiddenUnits * numClasses;
this.numNodeFeatures = numNodeFeatures;
this.numEdgeFeatures = numEdgeFeatures;
System.err.println("numOfEdgeFeatures: " + numEdgeFeatures);
this.useOutputLayer = flags.useOutputLayer;
this.useHiddenLayer = flags.useHiddenLayer;
this.useSigmoid = flags.useSigmoid;
this.docWindowLabels = new int[data.length][];
if (!useOutputLayer) {
System.err.println("Output layer not activated, inputLayerSize must be equal to numClasses, setting it to " + numClasses);
this.inputLayerSize = numClasses;
} else if (flags.softmaxOutputLayer && !(flags.sparseOutputLayer || flags.tieOutputLayer)) {
throw new RuntimeException("flags.softmaxOutputLayer == true, but neither flags.sparseOutputLayer or flags.tieOutputLayer is true");
}
empiricalCounts();
}
开发者ID:paulirwin，项目名称:Stanford.NER.Net，代码行数:35，代码来源:CRFNonLinearLogConditionalObjectiveFunction.java
示例11: NonLinearSecondOrderCliquePotentialFunction
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
public NonLinearSecondOrderCliquePotentialFunction(double[][] inputLayerWeights4Edge, double[][] outputLayerWeights4Edge, double[][] inputLayerWeights, double[][] outputLayerWeights, SeqClassifierFlags flags) {
this.inputLayerWeights4Edge = inputLayerWeights4Edge;
this.outputLayerWeights4Edge = outputLayerWeights4Edge;
this.inputLayerWeights = inputLayerWeights;
this.outputLayerWeights = outputLayerWeights;
this.flags = flags;
}
开发者ID:paulirwin，项目名称:Stanford.NER.Net，代码行数:8，代码来源:NonLinearSecondOrderCliquePotentialFunction.java
示例12: CRFNonLinearSecondOrderLogConditionalObjectiveFunction
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
CRFNonLinearSecondOrderLogConditionalObjectiveFunction(int[][][][] data, int[][] labels, int window, Index<String> classIndex, List<Index<CRFLabel>> labelIndices, int[] map, int prior, SeqClassifierFlags flags, int numNodeFeatures, int numEdgeFeatures) {
this.window = window;
this.classIndex = classIndex;
this.numClasses = classIndex.size();
this.labelIndices = labelIndices;
this.data = data;
this.flags = flags;
this.map = map;
this.labels = labels;
this.prior = prior;
this.backgroundSymbol = flags.backgroundSymbol;
this.sigma = flags.sigma;
this.outputLayerSize = numClasses;
this.outputLayerSize4Edge = numClasses * numClasses;
this.numHiddenUnits = flags.numHiddenUnits;
this.inputLayerSize = numHiddenUnits * numClasses;
this.inputLayerSize4Edge = numHiddenUnits * numClasses * numClasses;
this.numNodeFeatures = numNodeFeatures;
this.numEdgeFeatures = numEdgeFeatures;
this.useOutputLayer = flags.useOutputLayer;
this.useHiddenLayer = flags.useHiddenLayer;
this.useSigmoid = flags.useSigmoid;
this.docWindowLabels = new int[data.length][];
if (!useOutputLayer) {
System.err.println("Output layer not activated, inputLayerSize must be equal to numClasses, setting it to " + numClasses);
this.inputLayerSize = numClasses;
this.inputLayerSize4Edge = numClasses * numClasses;
} else if (flags.softmaxOutputLayer && !(flags.sparseOutputLayer || flags.tieOutputLayer)) {
throw new RuntimeException("flags.softmaxOutputLayer == true, but neither flags.sparseOutputLayer or flags.tieOutputLayer is true");
}
// empiricalCounts();
}
开发者ID:paulirwin，项目名称:Stanford.NER.Net，代码行数:33，代码来源:CRFNonLinearSecondOrderLogConditionalObjectiveFunction.java
示例13: hiddenLayerOutput
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
public static double[] hiddenLayerOutput(double[][] inputLayerWeights, int[] nodeCliqueFeatures, SeqClassifierFlags aFlag, double[] featureVal) {
int layerOneSize = inputLayerWeights.length;
double[] layerOne = new double[layerOneSize];
for (int i = 0; i < layerOneSize; i++) {
double[] ws = inputLayerWeights[i];
double lOneW = 0;
double dotProd = 0;
for (int m = 0; m < nodeCliqueFeatures.length; m++) {
dotProd = ws[nodeCliqueFeatures[m]];
if (featureVal != null)
dotProd *= featureVal[m];
lOneW += dotProd;
}
layerOne[i] = lOneW;
}
// transform layer one through hidden
double[] hiddenLayer = new double[layerOneSize];
for (int i = 0; i < layerOneSize; i++) {
if (aFlag.useHiddenLayer) {
if (aFlag.useSigmoid) {
hiddenLayer[i] = sigmoid(layerOne[i]);
} else {
hiddenLayer[i] = Math.tanh(layerOne[i]);
}
} else {
hiddenLayer[i] = layerOne[i];
}
}
return hiddenLayer;
}
开发者ID:benblamey，项目名称:stanford-nlp，代码行数:31，代码来源:NonLinearCliquePotentialFunction.java
示例14: CRFNonLinearLogConditionalObjectiveFunction
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
CRFNonLinearLogConditionalObjectiveFunction(int[][][][] data, int[][] labels, int window, Index<String> classIndex, List<Index<CRFLabel>> labelIndices, int[] map, SeqClassifierFlags flags, int numNodeFeatures, int numEdgeFeatures, double[][][][] featureVal) {
this.window = window;
this.classIndex = classIndex;
this.numClasses = classIndex.size();
this.labelIndices = labelIndices;
this.data = data;
this.featureVal = featureVal;
this.flags = flags;
this.map = map;
this.labels = labels;
this.prior = getPriorType(flags.priorType);
this.backgroundSymbol = flags.backgroundSymbol;
this.sigma = flags.sigma;
this.priorL1Lambda = flags.priorL1Lambda;
this.outputLayerSize = numClasses;
this.numHiddenUnits = flags.numHiddenUnits;
if (flags.arbitraryInputLayerSize != -1)
this.inputLayerSize = flags.arbitraryInputLayerSize;
else
this.inputLayerSize = numHiddenUnits * numClasses;
this.numNodeFeatures = numNodeFeatures;
this.numEdgeFeatures = numEdgeFeatures;
System.err.println("numOfEdgeFeatures: " + numEdgeFeatures);
this.useOutputLayer = flags.useOutputLayer;
this.useHiddenLayer = flags.useHiddenLayer;
this.useSigmoid = flags.useSigmoid;
this.docWindowLabels = new int[data.length][];
if (!useOutputLayer) {
System.err.println("Output layer not activated, inputLayerSize must be equal to numClasses, setting it to " + numClasses);
this.inputLayerSize = numClasses;
} else if (flags.softmaxOutputLayer && !(flags.sparseOutputLayer || flags.tieOutputLayer)) {
throw new RuntimeException("flags.softmaxOutputLayer == true, but neither flags.sparseOutputLayer or flags.tieOutputLayer is true");
}
empiricalCounts();
}
开发者ID:benblamey，项目名称:stanford-nlp，代码行数:36，代码来源:CRFNonLinearLogConditionalObjectiveFunction.java
示例15: init
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
public void init(SeqClassifierFlags flags) {
super.init(flags);
}
开发者ID:stanfordnlp，项目名称:phrasal，代码行数:4，代码来源:CRFPostprocessorFeatureFactory.java
示例16: init
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
@Override
public void init(SeqClassifierFlags flags) {}
开发者ID:stanfordnlp，项目名称:phrasal，代码行数:3，代码来源:ProcessorTools.java
示例17: StanfordTagger
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
public StanfordTagger(File file) throws Exception {
crf = new CRFClassifier<CoreLabel>(new SeqClassifierFlags());
crf.loadClassifierNoExceptions(file);
}
开发者ID:jdmp，项目名称:java-data-mining-package，代码行数:5，代码来源:StanfordTagger.java
示例18: NonLinearCliquePotentialFunction
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
public NonLinearCliquePotentialFunction(double[][] linearWeights, double[][] inputLayerWeights, double[][] outputLayerWeights, SeqClassifierFlags flags) {
this.linearWeights = linearWeights;
this.inputLayerWeights = inputLayerWeights;
this.outputLayerWeights = outputLayerWeights;
this.flags = flags;
}
开发者ID:paulirwin，项目名称:Stanford.NER.Net，代码行数:7，代码来源:NonLinearCliquePotentialFunction.java
示例19: hiddenLayerOutput
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
public double[] hiddenLayerOutput(double[][] inputLayerWeights, int[] nodeCliqueFeatures, SeqClassifierFlags aFlag, double[] featureVal, int cliqueSize) {
double[] layerCache = null;
double[] hlCache = null;
int layerOneSize = inputLayerWeights.length;
if (cliqueSize > 1) {
if (layerOneCache4Edge == null || layerOneSize != layerOneCache4Edge.length)
layerOneCache4Edge = new double[layerOneSize];
layerCache = layerOneCache4Edge;
} else {
if (layerOneCache == null || layerOneSize != layerOneCache.length)
layerOneCache = new double[layerOneSize];
layerCache = layerOneCache;
}
for (int i = 0; i < layerOneSize; i++) {
double[] ws = inputLayerWeights[i];
double lOneW = 0;
double dotProd = 0;
for (int m = 0; m < nodeCliqueFeatures.length; m++) {
dotProd = ws[nodeCliqueFeatures[m]];
if (featureVal != null)
dotProd *= featureVal[m];
lOneW += dotProd;
}
layerCache[i] = lOneW;
}
if (!aFlag.useHiddenLayer)
return layerCache;
// transform layer one through hidden
if (cliqueSize > 1) {
if (hiddenLayerCache4Edge == null || layerOneSize != hiddenLayerCache4Edge.length)
hiddenLayerCache4Edge = new double[layerOneSize];
hlCache = hiddenLayerCache4Edge;
} else {
if (hiddenLayerCache == null || layerOneSize != hiddenLayerCache.length)
hiddenLayerCache = new double[layerOneSize];
hlCache = hiddenLayerCache;
}
for (int i = 0; i < layerOneSize; i++) {
if (aFlag.useSigmoid) {
hlCache[i] = sigmoid(layerCache[i]);
} else {
hlCache[i] = Math.tanh(layerCache[i]);
}
}
return hlCache;
}
开发者ID:paulirwin，项目名称:Stanford.NER.Net，代码行数:48，代码来源:NonLinearSecondOrderCliquePotentialFunction.java
示例20: CMMClassifier
import edu.stanford.nlp.sequences.SeqClassifierFlags; //导入依赖的package包/类
protected CMMClassifier() {
super(new SeqClassifierFlags());
}
开发者ID:paulirwin，项目名称:Stanford.NER.Net，代码行数:4，代码来源:CMMClassifier.java
注：本文中的edu.stanford.nlp.sequences.SeqClassifierFlags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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