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Table 2 Classification results achieved on different feature subsets. The optimal values of σ and λ are also given.

From: A machine learning approach for the identification of odorant binding proteins from sequence-derived properties

Features

σ

λ

LOOA

BLOOA

TP rates

TN rates

MCC

1463

2.614e-5

1e-009

0.977

0.965

0.945

0.984

0.922

450

4.714e-5

1e-009

0.975

0.963

0.945

0.981

0.915

250

6.325e-5

1e-008

0.970

0.961

0.948

0.975

0.901

100

1e-4

1e-008

0.970

0.962

0.950

0.975

0.903

50

1.414e-4

1e-008

0.967

0.958

0.945

0.971

0.891

  1. LOOA – Leave-one-out accuracy (LOOA); BLOOA – Balanced LOOA MCC – Matthews Correlation Coefficient; σ – Kernel-parameter λ – Regularization parameter; TN – True negative; TP-True positive
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BMC Bioinformatics

ISSN: 1471-2105

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