- m_bestGoodness - Variable in class weka.attributeSelection.IWSS
-
Array which keeps the best cross-validation so far in the incremental
search
- m_dataset - Variable in class weka.attributeSelection.IWSS
-
The dataset
- m_formerSelected - Variable in class weka.attributeSelection.IWSS
-
Number of former attributes in ranking to be straight-forward selected
before running the incremental search.
- m_minFolds - Variable in class weka.attributeSelection.IWSS
-
Minimum number of folds in inner cross-validation whose wrapper goodness
must be improved when selecting a new attribute.
- m_numFolds - Static variable in class weka.attributeSelection.IWSS
-
Number of folds in the inner cross-validation
- m_numSelected - Variable in class weka.attributeSelection.IWSS
-
Number of selected attributes (first in ranking is selected by default)
- m_rankingMetric - Variable in class weka.attributeSelection.IWSS
-
Single Attribute evaluator used to create the ranking
- m_replaceSelection - Variable in class weka.attributeSelection.IWSS
-
Flag to activate the option of testing, at each step of the incremental
search, the swapping of a selected feature with another not selected yet.
- m_selected - Variable in class weka.attributeSelection.IWSS
-
Selected attributes
- m_skipRanking - Variable in class weka.attributeSelection.IWSS
-
It is set to true if IWSS.setStartSet is called
- m_testData - Variable in class weka.attributeSelection.IWSS
-
The test set for inner cross validation
- m_theta - Variable in class weka.attributeSelection.IWSS
-
Value for early stopping: (0-1] percentage of remaining attributes to
visit.
- m_trainingData - Variable in class weka.attributeSelection.IWSS
-
The training set for inner cross validation
- minFoldsTipText() - Method in class weka.attributeSelection.IWSS
-
Returns the tip text for this property