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[1] R. Kohavi and G. H. John. Wrappers for feature subset selection. ArtificialIntelligence, 97(12):273324, 1997.
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subset selectionFeatureInput
features AlgorithmInduction
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Feature selection search
estimation
Accuracy
EstimatedFinal EvaluationTest set
AlgorithmFeature set
Hypothesis
Performance
Training setTraining set
Feature evaluation
Induction Algorithm
Feature set
Feature setInduction
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0,0,1,1
0,0,0,0
1,0,0,0 0,1,0,0 0,0,1,0 0,0,0,1
1,1,0,0 1,0,1,0 0,1,1,0 1,0,0,1 0,1,0,1
1,1,1,0 1,1,0,1 1,0,1,1 0,1,1,1
1,1,1,1
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0,0,0,0
1,0,0,0 0,1,0,0 0,0,1,0 0,0,0,1
1,1,0,0 1,0,1,0 0,1,1,0 1,0,0,1 0,1,0,1 0,0,1,1
1,1,1,0 1,1,0,1 1,0,1,1 0,1,1,1
1,1,1,1
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100 200 300 400Nodes
crx - backward
76
7880
82
84
real acc
100 200 300 400Nodes
soybean - forward
20
40
60
80
real acc
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0 100 200 300 400 500 600 Nodes
Rand - forward selection
50
5560
65
70
75
80
Accuracy
0 20 40 60 80Nodes
Breast Cancer - forward selection
70
72
7476
78
80
82
Accuracy
0 20 40 60 80 100 Nodes
Glass2 - backward elimination
70
75
80
85
Accuracy
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