Japanese Credit Screening
Donated on 3/18/1992
Includes domain theory (generated by talking to Japanese domain experts); data in Lisp
Dataset Characteristics
Multivariate, Domain-Theory
Subject Area
Business
Associated Tasks
Classification
Feature Type
Categorical, Real, Integer
# Instances
125
# Features
15
Dataset Information
Additional Information
Examples represent positive and negative instances of people who were and were not granted credit. The theory was generated by talking to the individuals at a Japanese company that grants credit.
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| A1 | Feature | Categorical | yes | ||
| A2 | Feature | Continuous | yes | ||
| A3 | Feature | Continuous | no | ||
| A4 | Feature | Categorical | yes | ||
| A5 | Feature | Categorical | yes | ||
| A6 | Feature | Categorical | yes | ||
| A7 | Feature | Categorical | yes | ||
| A8 | Feature | Continuous | no | ||
| A9 | Feature | Binary | no | ||
| A10 | Feature | Binary | no |
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Dataset Files
| File | Size |
|---|---|
| crx.data | 31.5 KB |
| credit.lisp | 12 KB |
| crx.names | 1.5 KB |
| credit.names | 522 Bytes |
| Index | 182 Bytes |
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Install the ucimlrepo package
pip install ucimlrepo
Import the dataset into your code
View the full documentationfrom ucimlrepo import fetch_ucirepo # fetch dataset japanese_credit_screening = fetch_ucirepo(id=28) # data (as pandas dataframes) X = japanese_credit_screening.data.features y = japanese_credit_screening.data.targets # metadata print(japanese_credit_screening.metadata) # variable information print(japanese_credit_screening.variables)
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Citation
Sano, C. (1992). Japanese Credit Screening [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5259N.
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Keywords
Creators
Chiharu Sano
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.