本文整理汇总了Java中weka.classifiers.evaluation.NominalPrediction类的典型用法代码示例。如果您正苦于以下问题：Java NominalPrediction类的具体用法？Java NominalPrediction怎么用？Java NominalPrediction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。
NominalPrediction类属于weka.classifiers.evaluation包，在下文中一共展示了NominalPrediction类的3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，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: computeAccuracyAndRecordPrediction
import weka.classifiers.evaluation.NominalPrediction; //导入依赖的package包/类
public double computeAccuracyAndRecordPrediction(BayesianNetwork bn, DataOnMemory<DataInstance> data){
double correctPredictions = 0;
Variable classVariable = bn.getVariables().getVariableById(nb_.getClassIndex());
VMP vmp = new VMP();
vmp.setModel(bn);
for (DataInstance instance : data) {
double realValue = instance.getValue(classVariable);
instance.setValue(classVariable, Utils.missingValue());
vmp.setEvidence(instance);
vmp.runInference();
Multinomial posterior = vmp.getPosterior(classVariable);
if (Utils.maxIndex(posterior.getProbabilities())==realValue)
correctPredictions++;
Prediction prediction = new NominalPrediction(realValue, posterior.getProbabilities());
predictions.add(prediction);
instance.setValue(classVariable, realValue);
}
return correctPredictions/data.getNumberOfDataInstances();
}
示例2: evaluateModelOnceAndRecordPrediction
import weka.classifiers.evaluation.NominalPrediction; //导入依赖的package包/类
/**
* Evaluates the supplied distribution on a single instance.
*
* @param dist the supplied distribution
* @param instance the test instance to be classified
* @return the prediction
* @throws Exception if model could not be evaluated successfully
*/
public double evaluateModelOnceAndRecordPrediction(double[] dist,
Instance instance) throws Exception {
double pred;
if (m_ClassIsNominal) {
if (m_Predictions == null) {
m_Predictions = new FastVector();
}
pred = Utils.maxIndex(dist);
if (dist[(int) pred] <= 0) {
pred = Instance.missingValue();
}
updateStatsForClassifier(dist, instance);
m_Predictions.addElement(new NominalPrediction(instance.classValue(),
dist, instance.weight()));
} else {
pred = dist[0];
updateStatsForPredictor(pred, instance);
}
return pred;
}
示例3: calculateAccuracy
import weka.classifiers.evaluation.NominalPrediction; //导入依赖的package包/类
public static double calculateAccuracy(FastVector predictions) {
double correct = 0;
for (int i = 0; i < predictions.size(); i++) {
NominalPrediction np = (NominalPrediction) predictions.elementAt(i);
if (np.predicted() == np.actual()) {
correct++;
}
}
return 100 * correct / predictions.size();
}