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Table 5 Performance evaluation of the over-sampling method in terms of sensitivity and specificity

From: Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval

 

Sensitivity

Specificity

# of terms

SVM

Logistic

Ridge

SVM

Logistic

Ridge

10

0.6544 ± 0.026

0.6494 ± 0.027

0.6288 ± 0.020

0.8577 ± 0.012

0.8580 ± 0.012

0.8586 ± 0.015

20

0.4796 ± 0.020

0.5051 ± 0.020

0.4736 ± 0.019

0.9260 ± 0.006

0.9235 ± 0.006

0.9284 ± 0.007

30

0.3487 ± 0.023

0.3741 ± 0.024

0.3643 ± 0.035

0.9484 ± 0.004

0.9447 ± 0.005

0.9265 ± 0.032

40

0.2831 ± 0.017

0.3291 ± 0.018

0.2791 ± 0.026

0.9563 ± 0.004

0.9385 ± 0.004

0.9406 ± 0.023

50

0.2958 ± 0.024

0.3582 ± 0.025

0.2214 ± 0.025

0.9466 ± 0.006

0.9089 ± 0.010

0.9569 ± 0.023

  1. Sparse feature is used and the classification performance on stage range 11-12 is reported. Three different classifiers are applied for comparison, namely, SVM with linear kernel (SVM), logistic regression (Logistic) and ridge regression (Ridge).
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BMC Bioinformatics

ISSN: 1471-2105

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