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Table 4 Comparison of kernels in terms of maximum Az value of calcification dataset

From: AdaBoost-based multiple SVM-RFE for classification of mammograms in DDSM

kernel type

MGH

WU

WUFSM

SHH

 

8

22

8

22

8

22

8

22

linear

0.72686

0.72625

0.89981

0.90870

0.74046

0.77509

0.89603

0.92705

RBF

0.91042

0.76826

0.99192

0.88155

0.93625

0.89079

0.96280

0.94826

C

1

10

1

5

10

20

10

10

γ

1.5

0.1

1

0.05

0.4

0.05

0.15

0.05

  1. Same tradeoff parameter value C is used for both linear and RBF kernels.
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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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