Skip to main content

Table 1 PMLB results by [30]

From: Investigating the parameter space of evolutionary algorithms

Problem

Features

Classes

Samples

(a) “Easier” problems

mofn-3-7-10

10

2

1324

Clean2

168

2

6598

Clean1

168

2

476

Mushroom

22

2

8124

Irish

5

2

500

Agaricus-lepiota

22

2

8145

Corral

6

2

160

xd6

9

2

973

mux6

6

2

128

ThreeOf9

9

2

512

(b) “Harder” problems

Breast-cancer-wisconsin

30

2

569

wdbc

30

2

569

Tokyo1

44

2

959

New-thyroid

5

3

215

Spambase

57

2

4601

Vote

16

2

435

Soybean

35

18

675

House-votes-84

16

2

435

Breast-w

9

2

699

Molecular-biology_promoters

58

2

106

  1. (a) “Easier” problems: 10 datasets for which a balanced accuracy of 1 was attained most frequently.
  2. (b) “Harder” problems: 10 datasets whose average balanced accuracy was in the range [0.9,0.95]. Shown for each problem: number of features, number of classes, and number of samples
Back to article page

BioData Mining

ISSN: 1756-0381