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CrossValidationSplitResultProducer
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How to use
CrossValidationSplitResultProducer
in
weka.experiment

Best Java code snippets using weka.experiment.CrossValidationSplitResultProducer (Showing top 4 results out of 315)

origin: Waikato/weka-trunk

/**
 * Gets a text descrption of the result producer.
 * 
 * @return a text description of the result producer.
 */
@Override
public String toString() {
 String result = "CrossValidationSplitResultProducer: ";
 result += getCompatibilityState();
 if (m_Instances == null) {
  result += ": <null Instances>";
 } else {
  result += ": " + Utils.backQuoteChars(m_Instances.relationName());
 }
 return result;
}
origin: nz.ac.waikato.cms.weka/weka-stable

public void doRun(int run) throws Exception {
 if (getRawOutput()) {
  if (m_ZipDest == null) {
   m_ZipDest = new OutputZipper(m_OutputFile);
   Object[] seResults = m_SplitEvaluator.getResult(train, test);
   Object[] results = new Object[seResults.length + 1];
   results[0] = getTimestamp();
   System.arraycopy(seResults, 0, results, 1, seResults.length);
   if (m_debugOutput) {
origin: Waikato/weka-trunk

public void doRun(int run) throws Exception {
 if (getRawOutput()) {
  if (m_ZipDest == null) {
   m_ZipDest = new OutputZipper(m_OutputFile);
   Object[] seResults = m_SplitEvaluator.getResult(train, test);
   Object[] results = new Object[seResults.length + 1];
   results[0] = getTimestamp();
   System.arraycopy(seResults, 0, results, 1, seResults.length);
   if (m_debugOutput) {
origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Gets a text descrption of the result producer.
 * 
 * @return a text description of the result producer.
 */
@Override
public String toString() {
 String result = "CrossValidationSplitResultProducer: ";
 result += getCompatibilityState();
 if (m_Instances == null) {
  result += ": <null Instances>";
 } else {
  result += ": " + Utils.backQuoteChars(m_Instances.relationName());
 }
 return result;
}
weka.experimentCrossValidationSplitResultProducer

Javadoc

Carries out one split of a repeated k-fold cross-validation, using the set SplitEvaluator to generate some results. Note that the run number is actually the nth split of a repeated k-fold cross-validation, i.e. if k=10, run number 100 is the 10th fold of the 10th cross-validation run. This producer's sole purpose is to allow more fine-grained distribution of cross-validation experiments. If the class attribute is nominal, the dataset is stratified.

Valid options are:

 
-X <number of folds> 
The number of folds to use for the cross-validation. 
(default 10) 
 
-D 
Save raw split evaluator output. 
 
-O <file/directory name/path> 
The filename where raw output will be stored. 
If a directory name is specified then then individual 
outputs will be gzipped, otherwise all output will be 
zipped to the named file. Use in conjuction with -D. (default splitEvalutorOut.zip) 
 
-W <class name> 
The full class name of a SplitEvaluator. 
eg: weka.experiment.ClassifierSplitEvaluator 
 
Options specific to split evaluator weka.experiment.ClassifierSplitEvaluator: 
 
-W <class name> 
The full class name of the classifier. 
eg: weka.classifiers.bayes.NaiveBayes 
 
-C <index> 
The index of the class for which IR statistics 
are to be output. (default 1) 
 
-I <index> 
The index of an attribute to output in the 
results. This attribute should identify an 
instance in order to know which instances are 
in the test set of a cross validation. if 0 
no output (default 0). 
 
-P 
Add target and prediction columns to the result 
for each fold. 
 
Options specific to classifier weka.classifiers.rules.ZeroR: 
 
-D 
If set, classifier is run in debug mode and 
may output additional info to the console 
All options after -- will be passed to the split evaluator.

Most used methods

  • getCompatibilityState
  • getRawOutput
  • getTimestamp

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