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credit-g
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credit-g
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ARFF
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Uploaded 20-11-2024 by
Sebastian Silva Ruiz
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Finantial dataset for automl benchmark. Dataset 31 with target column class
21 features
class
(target)
nominal
2 unique values
0 missing
checking_status
nominal
4 unique values
0 missing
duration
numeric
33 unique values
0 missing
credit_history
nominal
5 unique values
0 missing
purpose
nominal
10 unique values
0 missing
credit_amount
numeric
921 unique values
0 missing
savings_status
nominal
5 unique values
0 missing
employment
nominal
5 unique values
0 missing
installment_commitment
numeric
4 unique values
0 missing
personal_status
nominal
4 unique values
0 missing
other_parties
nominal
3 unique values
0 missing
residence_since
numeric
4 unique values
0 missing
property_magnitude
nominal
4 unique values
0 missing
age
numeric
53 unique values
0 missing
other_payment_plans
nominal
3 unique values
0 missing
housing
nominal
3 unique values
0 missing
existing_credits
numeric
4 unique values
0 missing
job
nominal
4 unique values
0 missing
num_dependents
string
2 unique values
0 missing
own_telephone
string
2 unique values
0 missing
foreign_worker
string
2 unique values
0 missing
Show all 21 features
19 properties
NumberOfInstances
1000
Number of instances (rows) of the dataset.
NumberOfFeatures
21
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
12
Number of nominal attributes.
PercentageOfBinaryFeatures
4.76
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
AutoCorrelation
0.57
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
28.57
Percentage of numeric attributes.
MajorityClassPercentage
70
Percentage of instances belonging to the most frequent class.
PercentageOfSymbolicFeatures
57.14
Percentage of nominal attributes.
MajorityClassSize
700
Number of instances belonging to the most frequent class.
MinorityClassPercentage
30
Percentage of instances belonging to the least frequent class.
MinorityClassSize
300
Number of instances belonging to the least frequent class.
NumberOfBinaryFeatures
1
Number of binary attributes.
Show all 19 properties
1 tasks
Supervised Classification on credit-g
0 runs
- estimation_procedure: 10-fold Crossvalidation - target_feature: class
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