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Table 2 Experimental results on the DNA-protein sequence data set. Experimental results with Naive Bayes (NB) and Logistic Regression (LR) models, and Mixture of Experts (ME) models on the non-redundant DNA-protein sequence data set, where the identity cutoffs are 30% and 90%. The results are shown for default threshold θ = 0.5. ME-NB-global and ME-LR-global use NB and LR at the leaves and exploits the global sequence similarity to construct the hierarchical structure. ME-NB-local exploits the local sequence similarity to construct the hierarchical structure. ME-NB-random randomizes the global similarity matrix and constructs the hierarchical structure based on the randomized matrix.

From: Mixture of experts models to exploit global sequence similarity on biomolecular sequence labeling

Classifier

DNA-protein 30%

DNA-protein 90%

Precision

Recall

CC

FM

AUC

Precision

Recall

CC

FM

AUC

NB

0.59

0.05

0.16

0.10

0.75

0.56

0.07

0.18

0.13

0.75

ME-NB-global

0.62

0.12

0.25

0.20

0.77

0.65

0.15

0.29

0.25

0.78

ME-NB-local

0.65

0.06

0.18

0.12

0.76

0.64

0.08

0.21

0.15

0.76

ME-NB-random

0.58

0.05

0.15

0.09

0.75

0.56

0.07

0.18

0.13

0.75

LR

0.57

0.07

0.18

0.12

0.79

0.57

0.08

0.18

0.14

0.79

ME-LR-global

0.57

0.14

0.26

0.23

0.80

0.63

0.17

0.29

0.26

0.81