Saltar navegación Este enlace salta al contenido informativo de la página
Ir a página principal de um.es
      NEWS



  • Homage to Lofti A. Zadeh

    At IPMU2018 a well-deserved homage will be paid to his scientific work.
    Cádiz, Spain, June 11th - 15th, 2018

  • ISAPEP'21

    5th I W on Intelligent Systems for Agriculture Production and Environment Protection
    Dubai, United Arab Emirates, June 21th - 22th, 2021

  • NIP
    NIP-Software tool to manage
    low quality datasets
    © Univ. Murcia 2012
    R.P.I. nº 8/2012/700

  • FCTA 2011
    Best Student Paper Award
    "Constructing Fuzzy Partitions from Imprecise Data"
    J.M. Cadenas, M.C. Garrido, R. Martinez

  • FCTA 2012
    Best Paper Award
    "Towards an Approach to Select Features from Low Quality Datasets"
    J.M. Cadenas, M.C. Garrido, R. Martinez

DataSets repository

Datasets with imperfect values

Citation this paper for the use fo these datasets

J.M. Cadenas, M.C. Garrido, R. Martinez.
Feature subset selection Filter-Wrapper based on low quality data.
Expert Systems with Applications 40(16), 6241-6252, 2013.

Datasets interval-fuzzy values

Below you can find all the Classification datasets available. For each dataset, it is shown its name, attributes (the table details the number of Real/Nominal attributes in the data), number of instances, and classes (number of possible values of the output variable).

In addition, the table shows if the corresponding dataset has missing values, interval values, fuzzy values and/or noise (the table shows the percentage of low quality values).

The table allows to download each dataset (inside a ZIP file). Additionally, it is possible to obtain the dataset already partitioned, by means of a 10-folds / 5-folds cross validation procedure. Finally, we provide a file to give additional information about each dataset and its attributes (this information is available online at the logo or pdf file at the info.txt logo).

with interval values


Name #Attributes
(R/N)
#Examp. #Class. Missing
values
Interval
values
Dataset 3x5fcv
info.txt
(AUS) Australian
14  (6/8)
690
2
No
Yes (10%)
zip.gif
zip.gif
(BCW) Wisconsin Br. Cancer
 9  (9/0)
699
2
Yes (3%)*
Yes (10%)
zip.gif
info.txt
info.txt
(GER) German credit
24 (24/0)
1000
2
No
Yes (10%)
zip.gif
zip.gif
(GLA) Glass identification
 9  (9/0)
214
7
No
Yes (10%)
zip.gif
zip.gif
(HEA) Statlog Heart
13 (13/0)
270
2
No
Yes (10%)
zip.gif
zip.gif
(ION) Ionosphere
34 (34/0)
351
2
No
Yes (10%)
zip.gif
zip.gif
(IRP) Iris Plant
 4  (4/0)
150
3
No
Yes (10%)
zip.gif
zip.gif
(PIM) Pima Indian Diabetes
 8  (8/0)
768
2
No
Yes (10%)
zip.gif
zip.gif
(SON) Sonar
60 (60/0)
208
2
No
Yes (10%)
zip.gif
zip.gif
(SPE) Spectft heart
44 (44/0)
267
2
No
Yes (10%)
zip.gif
zip.gif
(VEH) Vehicle
18 (18/0)
846
4
No
Yes (10%)
zip.gif
zip.gif
(WDC) Wisconsin Diag. Br. Cancer
31 (31/0)
569
2
No
Yes (10%)
zip.gif
zip.gif
(WIN) Wine
13 (13/0)
178
3
No
Yes (10%)
zip.gif
zip.gif
(ZOO) Zoo
16 (1/16)
101
7
No
Yes (10%)
zip.gif
zip.gif
All datasets
zip.gif
info.txt


Go to "Datasets Repository"
 
Go to "DataSets and Results repository"

with fuzzy values

Name #Attributes
(R/N)
#Examp. #Class. Missing
values
Fuzzy
values
Dataset 3x5fcv
info.txt
(AUS) Australian
14  (6/8)
690
2
No
Yes (10%)
zip.gif
zip.gif
(BCW) Wisconsin Br. Cancer
 9  (9/0)
699
2
Yes (3%)*
Yes (10%)
zip.gif
zip.gif
info.txt
(GER) German credit
24 (24/0)
1000
2
No
Yes (10%)
zip.gif
zip.gif
(GLA) Glass identification
 9  (9/0)
214
7
No
Yes (10%)
zip.gif
zip.gif
(HEA) Statlog Heart
13 (13/0)
270
2
No
Yes (10%)
zip.gif
zip.gif
(ION) Ionosphere
34 (34/0)
351
2
No
Yes (10%)
zip.gif
zip.gif
(IRP) Iris Plant
 4  (4/0)
150
3
No
Yes (10%)
zip.gif
zip.gif
(PIM) Pima Indian Diabetes
 8  (8/0)
768
2
No
Yes (10%)
zip.gif
zip.gif
(SON) Sonar
60 (60/0)
208
2
No
Yes (10%)
zip.gif
zip.gif
(SPE) Spectft heart
44 (44/0)
267
2
No
Yes (10%)
zip.gif
zip.gif
(VEH) Vehicle
18 (18/0)
846
4
No
Yes (10%)
zip.gif
zip.gif
(WDC) Wisconsin Diag. Br. Cancer
31 (31/0)
569
2
No
Yes (10%)
zip.gif
zip.gif
(WIN) Wine
13 (13/0)
178
3
No
Yes (10%)
zip.gif
zip.gif
(ZOO) Zoo
16 (1/16)
101
7
No
Yes (10%)
zip.gif
zip.gif
All datasets
zip.gif
info.txt


Go to "Datasets Repository"
 
Go to "DataSets and Results repository"