This page provides the datasets and partitions used in the paper:
Weight Selection Strategies for Orderd Weighted Average Based Fuzzy Rough Sets
S. Vluymans, N. Mac Parthaláin, C. Cornelis, Y. Saeys
Submitted to Information Sciences

Corresponding author: sarah.vluymans@ugent.be

Datasets

In this paper, our proposed OWA weight selection guidelines were validated on 20 independent datasets, taken from the KEEL, UCI and WEKA dataset repositories. A zip-file containing these datasets and the partitions used in the paper is available for download here. Their characteristics are described in the table below. For each dataset, we list the number of features (nFeat), number of instances (nInst), number of classes (nCl) and the imbalance ratio (IR). We also specify whether or not all features are nominal.

Dataset description
Name nFeat All nominal? nInst nCl IR
appendicitis 7 No 106 2 4.05
banknote 7 No 1372 2 1.25
biodeg 40 No 1055 2 1.96
credit 15 No 653 2 1.21
ctg 21 No 2126 10 10.92
eye_detection 14 No 14980 2 1.23
faults 32 No 1941 2 1.88
grub 8 No 155 4 2.58
hepatitis 19 No 80 2 5.15
housevotes 16 Yes 232 2 1.15
iris 4 No 150 3 1
letter 16 No 20000 26 1.11
magic 10 No 19020 26 1.11
messidor 19 No 1151 2 1.13
mushroom 22 Yes 5644 2 1.62
optdigits 64 No 5620 10 1.03
penbased 16 No 10992 10 1.08
seismic 18 No 2584 2 14.2
sensor 24 No 5456 4 6.72
transfusion 4 No 748 2 3.2

Results

The full results for the FRPS and POSNN methods, discussed in Section 5.4 of the paper, can be found here.
Sarah VluymansSarah Vluymans