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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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