Data
ELE-2

ELE-2

active ARFF Public Domain (CC0) Visibility: public Uploaded 19-04-2020 by Rafael Gomes Mantovani
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Electrical-Maintenance data set This problem consists of four input variables and the available data set is comprised of a representative number of well distributed examples. In this case, the learning methods are expected to obtain a considerable number of rules. Therefore, this problem involves a larger search space (high complexity). ###Attributes 1. X1 - real [0.5,11.0] 2. X2 - real [0.15,8.55] 3. X3 - real [1.64,142.5] 4. X4 - real [1.0,165.0] 5. Y - real [64.470001,8546.030273]

5 features

Y (target)numeric1011 unique values
0 missing
X1numeric15 unique values
0 missing
X2numeric37 unique values
0 missing
X3numeric72 unique values
0 missing
X4numeric47 unique values
0 missing

19 properties

1056
Number of instances (rows) of the dataset.
5
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
5
Number of numeric attributes.
0
Number of nominal attributes.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
-1937.9
Average class difference between consecutive instances.
100
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
0
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.

9 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: Y
0 runs - estimation_procedure: 33% Holdout set - target_feature: Y
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
Define a new task