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Table 4 Performance evaluation 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

0.6211 ± 0.020

0.6267 ± 0.023

0.6307 ± 0.020

0.8520 ± 0.012

0.8460 ± 0.012

0.8323 ± 0.012

20

0.4633 ± 0.020

0.4483 ± 0.020

0.4441 ± 0.017

0.9252 ± 0.006

0.9354 ± 0.006

0.9309 ± 0.006

30

0.3306 ± 0.025

0.3154 ± 0.023

0.3038 ± 0.019

0.9523 ± 0.004

0.9566 ± 0.004

0.9573 ± 0.004

40

0.2549 ± 0.015

0.2424 ± 0.014

0.2320 ± 0.012

0.9628 ± 0.003

0.9677 ± 0.003

0.9668 ± 0.003

50

0.2032 ± 0.012

0.1974 ± 0.011

0.1910 ± 0.012

0.9724 ± 0.003

0.9732 ± 0.003

0.9723 ± 0.003

  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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