本文整理了Java中libsvm.svm.svm_get_labels()
方法的一些代码示例,展示了svm.svm_get_labels()
的具体用法。这些代码示例主要来源于Github
/Stackoverflow
/Maven
等平台,是从一些精选项目中提取出来的代码,具有较强的参考意义,能在一定程度帮忙到你。svm.svm_get_labels()
方法的具体详情如下:
包路径:libsvm.svm
类名称:svm
方法名:svm_get_labels
暂无
代码示例来源:origin: datumbox/datumbox-framework
svm.svm_get_labels(model,labels);
代码示例来源:origin: net.sourceforge/javaml
public int[] getLabels() {
int res[] = new int[model.nr_class];
svm.svm_get_labels(model, res);
return res;
}
代码示例来源:origin: org.apache.ctakes/ctakes-coreference
public AbstractClassifier(File fn, int len) {
try{
svmCls = svm.svm_load_model(fn.getAbsolutePath());
int[] labels = new int[2];
svm.svm_get_labels(svmCls, labels);
clsIndex = labels[0]==1 ? 0 : 1;
}catch(IOException e){
e.printStackTrace();
}
}
代码示例来源:origin: apache/ctakes
public AbstractClassifier(File fn, int len) {
try{
svmCls = svm.svm_load_model(fn.getAbsolutePath());
int[] labels = new int[2];
svm.svm_get_labels(svmCls, labels);
clsIndex = labels[0]==1 ? 0 : 1;
}catch(IOException e){
e.printStackTrace();
}
}
代码示例来源:origin: org.apache.ctakes/ctakes-coreference
private double calcAnaphoricity (JCas aJCas, Markable m) {
svm_node[] nodes = createAnaphoricityVector(m, aJCas);
double[] prob = new double[2];
svm.svm_predict_probability(anaph_model, nodes, prob);
int[] labels = new int[2];
svm.svm_get_labels(anaph_model, labels);
int anaph_idx = labels[0]==1 ? 0 : 1;
return prob[anaph_idx];
}
代码示例来源:origin: apache/ctakes
private double calcAnaphoricity (JCas aJCas, Markable m) {
svm_node[] nodes = createAnaphoricityVector(m, aJCas);
double[] prob = new double[2];
svm.svm_predict_probability(anaph_model, nodes, prob);
int[] labels = new int[2];
svm.svm_get_labels(anaph_model, labels);
int anaph_idx = labels[0]==1 ? 0 : 1;
return prob[anaph_idx];
}
代码示例来源:origin: education-service/speech-mfcc
public double classifyInstance(Observation observation, svm_model model) {
List<Double> features = observation.getFeatures();
svm_node[] nodes = new svm_node[observation.getFeatures().size()];
for (int i = 0; i < features.size(); i++) {
svm_node node = new svm_node();
node.index = i + 1;
node.value = features.get(i);
nodes[i] = node;
}
int[] labels = new int[TOTAL_CLASSES];
svm.svm_get_labels(model, labels);
double[] prob_estimates = new double[TOTAL_CLASSES];
return svm.svm_predict_probability(model, nodes, prob_estimates);
}
}
代码示例来源:origin: jzy3d/jzy3d-api
svm.svm_get_labels(model,labels);
prob_estimates = new double[nr_class];
代码示例来源:origin: org.maochen.nlp/CoreNLP-NLP
@Override
public Map<String, Double> predict(Tuple predict) {
double[] feats = predict.vector.getVector();
svm_node[] svmfeats = new svm_node[feats.length];
for (int i = 0; i < feats.length; i++) {
svm_node svmfeatI = new svm_node();
svmfeatI.index = i;
svmfeatI.value = feats[i];
svmfeats[i] = svmfeatI;
}
int totalSize = labelIndexer.getLabelSize();
int[] labels = new int[totalSize];
svm.svm_get_labels(model, labels);
double[] probs = new double[totalSize];
svm.svm_predict_probability(model, svmfeats, probs);
Map<String, Double> result = new HashMap<>();
for (int i = 0; i < labels.length; i++) {
result.put(labelIndexer.getLabel(labels[i]), probs[i]);
}
return result;
}
代码示例来源:origin: ch.epfl.bbp.nlp/bluima_jsre
svm.svm_get_labels(model,labels);
prob_estimates = new double[nr_class];
output.writeBytes("labels");
代码示例来源:origin: dkpro/dkpro-tc
svm.svm_get_labels(model, labels);
prob_estimates = new double[nr_class];
output.writeBytes("labels");
代码示例来源:origin: org.dkpro.tc/dkpro-tc-ml-libsvm
svm.svm_get_labels(model, labels);
prob_estimates = new double[nr_class];
output.writeBytes("labels");
代码示例来源:origin: org.clulab/processors
svm.svm_get_labels(model, labels);
int k = nr_class-1;
if (kBestList.getK() != -1) {
代码示例来源:origin: org.maltparser/maltparser
svm.svm_get_labels(model, labels);
int k = nr_class-1;
if (kBestList.getK() != -1) {
代码示例来源:origin: DigitalPebble/TextClassification
int nr_class = svm.svm_get_nr_class(model);
int[] labels = new int[nr_class];
svm.svm_get_labels(model, labels);
boolean support_probabilities = svm.svm_check_probability_model(model) == 1;
double[] scores = new double[nr_class];
代码示例来源:origin: jdmp/java-data-mining-package
svm.svm_get_labels(model, label);
Matrix output = Matrix.Factory.zeros(1, MathUtil.max(label) + 1);
代码示例来源:origin: nz.ac.waikato.cms.weka/LibSVM
svm.svm_get_labels(m_Model, labels);
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