unifeat.featureSelection.*
-
unifeat.featureSelection.embedded.SVMBasedMethods.MSVM_RFE
-
unifeat.featureSelection.embedded.SVMBasedMethods.OVA_SVM_RFE
private final double
1.0
private final double
0.001
-
unifeat.featureSelection.embedded.SVMBasedMethods.OVO_SVM_RFE
private final double
1.0
private final double
0.001
-
private final double
1.0E-4
-
unifeat.featureSelection.filter.supervised.GainRatio
private final double
1.0E-4
-
private final double
1.0E-4
-
private final double
1.0E-4
-
unifeat.featureSelection.filter.unsupervised.IRRFSACO_1
private final double
1.0E-4
private final double
1.0E-4
-
unifeat.featureSelection.filter.unsupervised.IRRFSACO_2
private final double
1.0E-4
private final double
1.0E-4
-
private final double
1.0E-4
-
unifeat.featureSelection.filter.unsupervised.MGSACO
private final double
1.0E-4
private final double
1.0E-4
-
unifeat.featureSelection.filter.unsupervised.RRFSACO_1
private final double
1.0E-4
private final double
1.0E-4
-
unifeat.featureSelection.filter.unsupervised.RRFSACO_2
private final double
1.0E-4
private final double
1.0E-4
-
unifeat.featureSelection.filter.unsupervised.UFSACO
private final double
1.0E-4
unifeat.gui.*
-
private static final double
0.25
private static final int
2
-
private static final int
1
-
private static final double
1.0
-
private static final int
5
private static final int
20
private static final double
1.0
-
"Option\n\nConfidence factor -> the confidence factor used for pruning (smaller values incur more pruning).\n\nMinNumSample -> the minimum number of samples per leaf.\n\n"
private static final double
0.25
private static final int
0
private static final int
2
private static final int
0
private static final int
100
private static final int
0
private static final int
0
private static final double
1.0
private static final double
0.001
"Option\n\nNum features -> the number of randomly selected features (0 means int(log_2(#predictors) + 1) is used).\n\nMax depth -- the maximum depth of the tree (0 means unlimited depth).\n\nNum iterations -- the number of iterations to be performed.\n\n"
"Option\n\nK value -> sets the number of randomly chosen attributes (0 means int(log_2(#predictors) + 1) is used).\n\nMax depth -- the maximum depth of the tree (0 means unlimited depth).\n\nMin num -- the minimum total weight of the instances in a leaf.\n\nMin variance prop -- the minimum proportion of the total variance (over all the data) required for split.\n\n"
-
private static final double
1.0
private static final double
0.2
private static final int
0
private static final int
0
private static final int
50
private static final double
0.7
-
private static final double
1.0
private static final double
1.0
private static final double
0.2
private static final double
0.2
private static final int
0
private static final int
0
private static final int
50
private static final double
0.7
-
private static final double
100.0
private static final int
5
-
private static final double
1.0
private static final double
0.2
private static final double
0.2
private static final int
0
private static final int
50
private static final double
0.7
-
private static final double
1.0
private static final double
0.2
private static final int
0
private static final int
0
private static final int
50
private static final double
0.7
-
private static final double
1.0
private static final double
1.0
private static final double
0.2
private static final double
0.2
private static final int
0
private static final int
0
private static final int
50
private static final double
0.7
-
unifeat.gui.featureSelection.filter.RRFSPanel
private static final double
0.4
-
private static final double
1.0
private static final double
0.2
private static final double
0.2
private static final int
0
private static final int
0
private static final int
50
private static final double
0.7
-
unifeat.gui.featureSelection.filter.rsm.RSMPanel
private static final int
0
private static final int
50
private static final int
0
-
private static final double
1.0
private static final double
0.8
-
unifeat.gui.featureSelection.wrapper.GABased.HGAFSPanel
private static final double
0.5
private static final double
0.65
-
unifeat.gui.featureSelection.wrapper.PSOBased.CPSOPanel
private static final double
0.6
-
private static final double
0.65
private static final double
0.5
-
unifeat.gui.featureSelection.wrapper.PSOBased.PSO42Panel
private static final double
0.6