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Table 3 Average improvements

From: Building gene expression profile classifiers with a simple and efficient rejection option in R

 

SOCMT

MOCV

  

K-NN-OC

KMeans-OC

PCA-OC

Parzen-OC

SVM-OC

K-NN-OC

KMeans-OC

PCA-OC

Parzen-OC

SVM-OC

G_3

K-NN+rule

+0.08

+0.01

-0.01

+ 0.01

+ 0.12

+ 0.04

+ 0.05

+0.01

+0.05

+0.11

 

RF+rule

+0.19

+0.12

+0.10

+0.12

+0.23

+0.15

+0.16

+0.12

+0.16

+0.22

 

N-NET+rule

+0.03

-0.04

-0.06

-0.04

+ 0.07

-0.01

+ 0.00

-0.04

+0.00

+0.06

G_4

K-NN+rule

-0.01

-0.05

-0.01

-0.05

+ 0.06

+ 0.10

-0.07

-0.08

+0.00

+0.03

 

RF+rule

+0.13

+0.09

+0.13

+0.09

+0.20

+0.24

+0.07

+0.06

+0.14

+0.17

 

N-NET+rule

+0.06

+0.02

+ 0.06

-0.04

0.13

+ 0.17

+ 0.00

-0.01

+0.00

0.1

G_5

K-NN+rule

-0.04

-0.16

-0.05

-0.15

-0.04

+ 0.04

-0.14

-0.14

-0.06

-0.05

 

RF+rule

+ 0.2

+0.08

+0.19

+0.09

+0.20

+0.28

+0.1

+ 0.1

+0.18

+0.19

 

N-NET+rule

+0.11

-0.01

+ 0.10

+ 0.00

+ 0.11

+ 0.19

+ 0.01

+0.01

+0.09

+0.10

G_6

K-NN+rule

+0.06

+0.01

+ 0.03

-0.07

+ 0.03

+ 0.07

+ 0.00

+0.01

+0.11

+0.10

 

RF+rule

+0.19

+0.14

+0.16

+ 0.06

+ 0.16

+0.20

+0.13

+0.14

+0.24

+0.23

 

N-NET+rule

+0.07

+0.02

+ 0.04

+ 0.01

+ 0.04

+ 0.08

+ 0.01

+0.02

+0.19

+0.11

  1. Results are provided in terms of improvement of the accuracy of multi-class classifiers with decision rules versus one-class classifiers.