Table 2 Statistical results for SP of the investigated techniques.

From: Efficient feature selection for histopathological image classification with improved multi-objective WOA

Benchmark problems

Approaches

Mean

Median

STDDev.

Worst

Best

UF1

MOPSO

0.009

0.009

0.003

0.015

0.007

MOEA/D

0.004

0.004

0.002

0.007

0.002

MOGWO

0.013

0.005

0.015

0.047

0.001

Proposed IMOWOA

0.013

0.012

0.004

0.021

0.010

UF2

MOPSO

0.008

0.008

0.002

0.013

0.006

MOEA/D

0.009

0.009

0.001

0.011

0.008

MOGWO

0.010

0.008

0.003

0.016

0.007

Proposed IMOWOA

0.011

0.010

0.004

0.018

0.008

UF3

MOPSO

0.007

0.007

0.002

0.010

0.005

MOEA/D

0.027

0.025

0.021

0.064

0.001

MOGWO

0.047

0.049

0.015

0.072

0.016

Proposed IMOWOA

0.053

0.056

0.017

0.081

0.018

UF4

MOPSO

0.007

0.007

0.001

0.008

0.006

MOEA/D

0.007

0.007

0.001

0.009

0.006

MOGWO

0.010

0.009

0.004

0.017

0.006

Proposed IMOWOA

0.011

0.010

0.004

0.020

0.007

UF5

MOPSO

0.005

0.005

0.004

0.012

0.000

MOEA/D

0.003

0.000

0.006

0.016

0.000

MOGWO

0.155

0.089

0.165

0.520

0.009

Proposed IMOWOA

0.173

0.100

0.185

0.583

0.010

UF6

MOPSO

0.021

0.013

0.033

0.113

0.002

MOEA/D

0.006

0.000

0.013

0.031

0.000

MOGWO

0.015

0.011

0.013

0.042

0.002

Proposed IMOWOA

0.017

0.013

0.014

0.048

0.002

UF7

MOPSO

0.007

0.007

0.003

0.013

0.003

MOEA/D

0.005

0.004

0.003

0.012

0.001

MOGWO

0.008

0.006

0.009

0.032

0.000

Proposed IMOWOA

0.009

0.006

0.010

0.036

0.000

UF8

MOPSO

0.027

0.027

0.008

0.045

0.016

MOEA/D

–

–

–

–

–

MOGWO

0.007

0.005

0.005

0.019

0.004

Proposed IMOWOA

0.030

0.029

0.009

0.050

0.017

UF9

MOPSO

0.024

0.024

0.004

0.031

0.017

MOEA/D

–

–

–

–

–

MOGWO

0.018

0.019

0.006

0.029

0.007

Proposed IMOWOA

0.020

0.021

0.007

0.032

0.007

UF10

MOPSO

0.020

0.021

0.004

0.027

0.016

MOEA/D

–

–

–

–

–

MOGWO

0.026

0.024

0.015

0.055

0.000

Proposed IMOWOA

0.022

0.023

0.004

0.030

0.017