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Table 5 TOPSIS scores of the prediction performance for the three different kernels

From: PredCRG: A computational method for recognition of plant circadian genes by employing support vector machine with Laplace kernel

Kernel

Q1

Q2

Q3

Q4

Overall

Linear

54.64

67.50

45.98

47.56

70.09

Laplace

61.12

59.85

58.11

41.67

73.20

Radial

40.78

31.75

24.98

57.91

23.77

  1. For Q1 and Q3, TOPSIS scores are higher for the Laplace kernel, whereas linear and RBF achieved higher scores for Q2 and Q4 respectively. While all the four sub-datasets are accounted, the Laplace kernel achieved higher TOPSIS score than the other two kernel functions
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Plant Methods

ISSN: 1746-4811