Student Loan Relational
Donated on 12/31/1992
Student Loan Relational Domain
Dataset Characteristics
Domain-Theory
Subject Area
Social Science
Associated Tasks
-
Feature Type
-
# Instances
1000
# Features
-
Dataset Information
Additional Information
The predicate no_payment_due/1 is true for those people who are not required to repay a student loan. Auxiliary relations can be used to fully discriminate positive from negative instances of no_payment_due/1. Closed world assumption applies to all auxiliary relations.
Has Missing Values?
No
Dataset Files
| File | Size |
|---|---|
| longest_absense_from_school.pl | 42 KB |
| enrolled.pl | 33.3 KB |
| no_payment_due.pl | 31.1 KB |
| enlist.pl | 9.5 KB |
| male.pl | 8.7 KB |
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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 student_loan_relational = fetch_ucirepo(id=99) # data (as pandas dataframes) X = student_loan_relational.data.features y = student_loan_relational.data.targets # metadata print(student_loan_relational.metadata) # variable information print(student_loan_relational.variables)
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Citation
Brunk, C. (1991). Student Loan Relational [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5CP53.
Style:
Creators
C. Brunk
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.