Data
pol

pol

active ARFF Publicly available Visibility: public Uploaded 05-07-2022 by Leo Grin
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Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "classification on numerical features" benchmark. Original description: Author: Source: Unknown - Date unknown Please cite: Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a lower target value as positive ('P') and all others as negative ('N').

27 features

binaryClass (target)nominal2 unique values
0 missing
f5numeric181 unique values
0 missing
f6numeric117 unique values
0 missing
f7numeric110 unique values
0 missing
f8numeric99 unique values
0 missing
f9numeric77 unique values
0 missing
f13numeric87 unique values
0 missing
f14numeric105 unique values
0 missing
f15numeric110 unique values
0 missing
f16numeric107 unique values
0 missing
f17numeric109 unique values
0 missing
f18numeric113 unique values
0 missing
f19numeric97 unique values
0 missing
f20numeric83 unique values
0 missing
f21numeric78 unique values
0 missing
f22numeric82 unique values
0 missing
f23numeric74 unique values
0 missing
f24numeric59 unique values
0 missing
f25numeric65 unique values
0 missing
f26numeric61 unique values
0 missing
f27numeric62 unique values
0 missing
f28numeric59 unique values
0 missing
f29numeric58 unique values
0 missing
f30numeric43 unique values
0 missing
f31numeric42 unique values
0 missing
f32numeric39 unique values
0 missing
f33numeric35 unique values
0 missing

19 properties

10082
Number of instances (rows) of the dataset.
27
Number of attributes (columns) of the dataset.
2
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.
26
Number of numeric attributes.
1
Number of nominal attributes.
3.7
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
1
Average class difference between consecutive instances.
96.3
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
3.7
Percentage of nominal attributes.
50
Percentage of instances belonging to the most frequent class.
5041
Number of instances belonging to the most frequent class.
50
Percentage of instances belonging to the least frequent class.
5041
Number of instances belonging to the least frequent class.
1
Number of binary attributes.

2 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
0 runs - estimation_procedure: 4-fold Crossvalidation - target_feature: binaryClass
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