OpenML
credit-approval

credit-approval

active ARFF Publicly available Visibility: public Uploaded 27-01-2023 by Young Lee
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This file concerns credit card applications. All attribute names and values have been changed to meaningless symbols to protect the confidentiality of the data.This dataset is interesting because there is a good mix of attributes -- continuous, nominal with small numbers of values, and nominal with larger numbers of values. There are also a few missing values.

16 features

class (target)string2 unique values
0 missing
A2numeric340 unique values
0 missing
A3numeric213 unique values
0 missing
A8numeric131 unique values
0 missing
A11numeric23 unique values
0 missing
A14numeric164 unique values
0 missing
A15numeric229 unique values
0 missing
A1nominal2 unique values
0 missing
A4nominal3 unique values
0 missing
A5nominal3 unique values
0 missing
A6nominal14 unique values
0 missing
A7nominal9 unique values
0 missing
A9nominal2 unique values
0 missing
A10nominal2 unique values
0 missing
A12nominal2 unique values
0 missing
A13nominal3 unique values
0 missing
Show all 16 features

19 properties

NumberOfInstances
653
Number of instances (rows) of the dataset.
NumberOfFeatures
16
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
6
Number of numeric attributes.
NumberOfSymbolicFeatures
9
Number of nominal attributes.
MajorityClassSize
357
Number of instances belonging to the most frequent class.
MinorityClassPercentage
45.33
Percentage of instances belonging to the least frequent class.
MinorityClassSize
296
Number of instances belonging to the least frequent class.
NumberOfBinaryFeatures
4
Number of binary attributes.
PercentageOfBinaryFeatures
25
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
AutoCorrelation
1
Average class difference between consecutive instances.
PercentageOfMissingValues
0
Percentage of missing values.
Dimensionality
0.02
Number of attributes divided by the number of instances.
PercentageOfNumericFeatures
37.5
Percentage of numeric attributes.
MajorityClassPercentage
54.67
Percentage of instances belonging to the most frequent class.
PercentageOfSymbolicFeatures
56.25
Percentage of nominal attributes.
Show all 19 properties

1 tasks

Supervised Classification on credit-approval
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
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