文件名称:fs_sup_fcbf
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Using Weka s feature selection algorithm
X, the features on current trunk, each colum is a feature vector on all
instances, and each row is a part of the instance
Y, the label of instances, in single column form: 1 2 3 4 5 ...
a.E = weka.attributeSelection.SymmetricalUncertAttributeSetEval
a.S = weka.attributeSelection.FCBFSearch -D false -T -1.7976931348623157E308 -N -1- Using Weka s feature selection algorithm
X, the features on current trunk, each colum is a feature vector on all
instances, and each row is a part of the instance
Y, the label of instances, in single column form: 1 2 3 4 5 ...
a.E = weka.attributeSelection.SymmetricalUncertAttributeSetEval
a.S = weka.attributeSelection.FCBFSearch -D false -T -1.7976931348623157E308 -N -1
X, the features on current trunk, each colum is a feature vector on all
instances, and each row is a part of the instance
Y, the label of instances, in single column form: 1 2 3 4 5 ...
a.E = weka.attributeSelection.SymmetricalUncertAttributeSetEval
a.S = weka.attributeSelection.FCBFSearch -D false -T -1.7976931348623157E308 -N -1- Using Weka s feature selection algorithm
X, the features on current trunk, each colum is a feature vector on all
instances, and each row is a part of the instance
Y, the label of instances, in single column form: 1 2 3 4 5 ...
a.E = weka.attributeSelection.SymmetricalUncertAttributeSetEval
a.S = weka.attributeSelection.FCBFSearch -D false -T -1.7976931348623157E308 -N -1
(系统自动生成,下载前可以参看下载内容)
下载文件列表
fs_sup_fcbf\fs_sup_fcbf\fsFCBF.m
...........\fs_sup_fcbf
fs_sup_fcbf