本文整理了Java中weka.core.Instances.firstInstance()
方法的一些代码示例,展示了Instances.firstInstance()
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。Instances.firstInstance()
方法的具体详情如下:
包路径:weka.core.Instances
类名称:Instances
方法名:firstInstance
[英]Returns the first instance in the set.
[中]返回集合中的第一个实例。
代码示例来源:origin: stackoverflow.com
Instances dataUnlabeled = new Instances("TestInstances", atts, 0);
dataUnlabeled.add(newInst);
dataUnlabeled.setClassIndex(dataUnlabeled.numAttributes() - 1);
double classif = ibk.classifyInstance(dataUnlabeled.firstInstance());
代码示例来源:origin: com.googlecode.obvious/obviousx-weka
@Override
public Instance firstInstance() {
return super.firstInstance();
}
代码示例来源:origin: Waikato/weka-trunk
/**
* Resets the class values of all instances using voting. For each instance
* the class value that satisfies the most rules is choosen as new class
* value.
*
* @param dataset the dataset to work on
* @return the changed instances
* @throws Exception if something goes wrong
*/
private Instances voteDataset(Instances dataset) throws Exception {
for (int i = 0; i < dataset.numInstances(); i++) {
Instance inst = dataset.firstInstance();
inst = votedReclassifyExample(inst);
dataset.add(inst);
dataset.delete(0);
}
return dataset;
}
代码示例来源:origin: nz.ac.waikato.cms.weka/weka-stable
/**
* Resets the class values of all instances using voting. For each instance
* the class value that satisfies the most rules is choosen as new class
* value.
*
* @param dataset the dataset to work on
* @return the changed instances
* @throws Exception if something goes wrong
*/
private Instances voteDataset(Instances dataset) throws Exception {
for (int i = 0; i < dataset.numInstances(); i++) {
Instance inst = dataset.firstInstance();
inst = votedReclassifyExample(inst);
dataset.add(inst);
dataset.delete(0);
}
return dataset;
}
代码示例来源:origin: stackoverflow.com
System.out.println(cls.classifyInstance(testing.firstInstance()));
代码示例来源:origin: hltfbk/Excitement-Open-Platform
result = classifier.classifyInstance(instances.firstInstance());
} catch (Exception e) {
throw new EDAException(e);
try {
confidence = Math.max(
classifier.distributionForInstance(instances.firstInstance())[0],
classifier.distributionForInstance(instances.firstInstance())[1]);
} catch (Exception e) {
throw new EDAException(e);
String label = instances.firstInstance().classAttribute().value(new Double(result).intValue()).toLowerCase();
代码示例来源:origin: net.sf.meka/meka
@Override
public double[] distributionForInstance(Instance xy) throws Exception {
int L = xy.classIndex();
double z[] = dbm.prob_z(MLUtils.getxfromInstance(xy));
Instance zy = (Instance)m_InstancesTemplate.firstInstance().copy();
MLUtils.setValues(zy,z,L);
zy.setDataset(m_InstancesTemplate);
return m_Classifier.distributionForInstance(zy);
}
代码示例来源:origin: Waikato/meka
@Override
public double[] distributionForInstance(Instance xy) throws Exception {
int L = xy.classIndex();
double z[] = dbm.prob_z(MLUtils.getxfromInstance(xy));
Instance zy = (Instance)m_InstancesTemplate.firstInstance().copy();
MLUtils.setValues(zy,z,L);
zy.setDataset(m_InstancesTemplate);
return m_Classifier.distributionForInstance(zy);
}
代码示例来源:origin: net.sf.meka/meka
@Override
public Instances process(Instances D) throws Exception {
//System.out.println("PROCESS! = "+D.numInstances());
int L = D.classIndex();
D = new Instances(D); // D_
// rename classes
for(int j = 0; j < L; j++) {
D.renameAttribute(j,encodeClass(j));
}
// merge labels
D = mergeLabels(D,indices,m_P,m_N);
// templates
x_template = D.firstInstance();
setOutputFormat(D);
//System.out.println("PROCESS! => "+D);
return D;
}
代码示例来源:origin: Waikato/meka
@Override
public Instances process(Instances D) throws Exception {
//System.out.println("PROCESS! = "+D.numInstances());
int L = D.classIndex();
D = new Instances(D); // D_
// rename classes
for(int j = 0; j < L; j++) {
D.renameAttribute(j,encodeClass(j));
}
// merge labels
D = mergeLabels(D,indices,m_P,m_N);
// templates
x_template = D.firstInstance();
setOutputFormat(D);
//System.out.println("PROCESS! => "+D);
return D;
}
代码示例来源:origin: nz.ac.waikato.cms.weka/multiInstanceLearning
/**
* Computes the distribution for a given exemplar
*
* @param newBag the exemplar for which distribution is computed
* @return the distribution
* @throws Exception if the distribution can't be computed successfully
*/
@Override
public double[] distributionForInstance(Instance newBag) throws Exception {
double[] distribution = new double[2];
Instances test = new Instances(newBag.dataset(), 0);
test.add(newBag);
test = transform(test);
test.deleteAttributeAt(0);
Instance newInst = test.firstInstance();
distribution = m_Classifier.distributionForInstance(newInst);
return distribution;
}
代码示例来源:origin: olehmberg/winter
double[] distribution = this.classifier.distributionForInstance(matchInstances.firstInstance());
int positiveClassIndex = matchInstances.attribute(matchInstances.classIndex()).indexOfValue("1");
double matchConfidence = distribution[positiveClassIndex];
代码示例来源:origin: net.sf.meka.thirdparty/mulan
protected void buildInternal(MultiLabelInstances trainingData) throws Exception {
baseLearner.build(trainingData);
MultiLabelOutput mlo = baseLearner.makePrediction(trainingData.getDataSet().firstInstance());
if (!mlo.hasRanking()) {
throw new MulanRuntimeException("Learner is not a ranker");
}
// by default set threshold equal to the rounded average cardinality
if (measure == null) {
t = (int) Math.round(trainingData.getCardinality());
t = 2;
} else {
// hold a reference to the trainingData in case of auto-tuning
if (folds == 0) {
double[] diff = computeThreshold(baseLearner, trainingData, measure);
t = Utils.minIndex(diff);
} else {
autoTuneThreshold(trainingData, measure, folds);
}
}
}
代码示例来源:origin: nz.ac.waikato.cms.weka/distributedWekaBase
irisData.firstInstance().setMissing(0); // set one value to missing
Instances irisSummaryHeader = getIrisSummaryHeader();
task.processInstance(irisData.firstInstance());
fail("Should have thrown an exception as we have not yet called init()");
} catch (DistributedWekaException e) {
task.processInstance(irisData.firstInstance());
fail("Should have thrown an exception as we have not set any starting centroids to use yet");
} catch (DistributedWekaException e) {
initialCenters.add(irisData.firstInstance());
initialCenters.add(irisData.instance(50));
initialCenters.add(irisData.instance(100));
代码示例来源:origin: nz.ac.waikato.cms.weka/distributedWekaBase
@Test
public void testInitializationDontReplaceMissing() throws Exception {
Instances irisData = CorrelationMatrixMapTaskTest.getIris();
irisData.firstInstance().setMissing(0); // set one value to missing
Instances irisSummaryHeader = getIrisSummaryHeader();
task.setDontReplaceMissingValues(true);
try {
task.processInstance(irisData.firstInstance());
fail("Should have thrown an exception as we have not yet called init()");
} catch (DistributedWekaException e) {
task.processInstance(irisData.firstInstance());
fail("Should have thrown an exception as we have not set any starting centroids to use yet");
} catch (DistributedWekaException e) {
initialCenters.add(irisData.firstInstance());
initialCenters.add(irisData.instance(50));
initialCenters.add(irisData.instance(100));
代码示例来源:origin: nz.ac.waikato.cms.weka/distributedWekaBase
initialCenters.add(irisData.firstInstance());
initialCenters.add(irisData.instance(50));
initialCenters.add(irisData.instance(100));
代码示例来源:origin: nz.ac.waikato.cms.weka/distributedWekaBase
initialCenters.add(irisData.firstInstance());
initialCenters.add(irisData.instance(50));
initialCenters.add(irisData.instance(100));
代码示例来源:origin: nz.ac.waikato.cms.weka/distributedWekaBase
initialCenters.add(irisData.firstInstance());
initialCenters.add(irisData.instance(50));
initialCenters.add(irisData.instance(100));
代码示例来源:origin: nz.ac.waikato.cms.weka/distributedWekaBase
initialCenters.add(irisData.firstInstance());
initialCenters.add(irisData.instance(50));
initialCenters.add(irisData.instance(100));
代码示例来源:origin: nz.ac.waikato.cms.weka/distributedWekaBase
@Test
public void testClusteringMissingValuesReplacementOnly() throws Exception {
Instances irisData = CorrelationMatrixMapTaskTest.getIris();
Instances irisSummaryHeader = getIrisSummaryHeader();
KMeansMapTask task = new KMeansMapTask();
task.init(irisSummaryHeader);
assertFalse(task.getDontReplaceMissingValues());
Instances initialCenters = new Instances(irisData, 0);
initialCenters.add(irisData.firstInstance());
initialCenters.add(irisData.instance(50));
initialCenters.add(irisData.instance(100));
initialCenters = task.applyFilters(initialCenters);
task.setCentroids(initialCenters);
// processInstance() should not raise exceptions now
for (int i = 0; i < irisData.numInstances(); i++) {
task.processInstance(irisData.instance(i));
}
List<Instances> centroidStats = task.getCentroidStats();
assertEquals(3, centroidStats.size());
// size of each should be 50 instances
for (Instances i : centroidStats) {
Attribute summary = i.attribute(5);
assertEquals(50,
(int) ArffSummaryNumericMetric.COUNT
.valueFromAttribute(summary));
}
}
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