Student Academics Performance
Donated on 9/15/2018
The dataset tried to find the end semester percentage prediction based on different social, economic and academic attributes.
Dataset Characteristics
Multivariate
Subject Area
Computer Science
Associated Tasks
Classification
Feature Type
-
# Instances
300
# Features
22
Dataset Information
Additional Information
Student Academic Performance Dataset
Has Missing Values?
No
Introductory Paper
By Sadiq Hussain, N. A. Dahan, F. Ba-Alwi, Najoua Ribata. 2018
Published in Indonesian Journal of Electrical Engineering and Computer Science
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| ge | Feature | Categorical | no | ||
| cst | Feature | Categorical | no | ||
| tnp | Feature | Categorical | no | ||
| twp | Feature | Categorical | no | ||
| iap | Feature | Categorical | no | ||
| esp | Feature | Categorical | no | ||
| arr | Feature | Categorical | no | ||
| ms | Feature | Categorical | no | ||
| ls | Feature | Categorical | no | ||
| as | Feature | Categorical | no |
0 to 10 of 22
Additional Variable Information
@ATTRIBUTE ge {M,F} @ATTRIBUTE cst {G,ST,SC,OBC,MOBC} @ATTRIBUTE tnp {Best,Vg,Good,Pass,Fail} @ATTRIBUTE twp {Best,Vg,Good,Pass,Fail} @ATTRIBUTE iap {Best,Vg,Good,Pass,Fail} @ATTRIBUTE esp {Best,Vg,Good,Pass,Fail} @ATTRIBUTE arr {Y,N} @ATTRIBUTE ms {Married,Unmarried} @ATTRIBUTE ls {T,V} @ATTRIBUTE as {Free,Paid} @ATTRIBUTE fmi {Vh,High,Am,Medium,Low} @ATTRIBUTE fs {Large,Average,Small} @ATTRIBUTE fq {Il,Um,10,12,Degree,Pg} @ATTRIBUTE mq {Il,Um,10,12,Degree,Pg} @ATTRIBUTE fo {Service,Business,Retired,Farmer,Others} @ATTRIBUTE mo {Service,Business,Retired,Housewife,Others} @ATTRIBUTE nf {Large,Average,Small} @ATTRIBUTE sh {Good,Average,Poor} @ATTRIBUTE ss {Govt,Private} @ATTRIBUTE me {Eng,Asm,Hin,Ben} @ATTRIBUTE tt {Large,Average,Small} @ATTRIBUTE atd {Good,Average,Poor}
Reviews
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset student_academics_performance = fetch_ucirepo(id=467) # data (as pandas dataframes) X = student_academics_performance.data.features y = student_academics_performance.data.targets # metadata print(student_academics_performance.metadata) # variable information print(student_academics_performance.variables)
Hussain,Sadiq. (2018). Student Academics Performance. UCI Machine Learning Repository. https://doi.org/10.24432/C50W30.
@misc{misc_student_academics_performance_467,
author = {Hussain,Sadiq},
title = {{Student Academics Performance}},
year = {2018},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C50W30}
}Creators
Sadiq Hussain
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.