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
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Download
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)
0 citations
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Citation
Brunk,C.. (1993). Student Loan Relational. UCI Machine Learning Repository. https://doi.org/10.24432/C5CP53.
BibTeX
@misc{misc_student_loan_relational_99,
author = {Brunk,C.},
title = {{Student Loan Relational}},
year = {1993},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5CP53}
}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.