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Analyzing Health Care Dataset using Machine Learning Techniques

by B. Tamilvanan, V. Murali Bhaskaran
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 158 - Number 8
Year of Publication: 2017
Authors: B. Tamilvanan, V. Murali Bhaskaran
10.5120/ijca2017912828

B. Tamilvanan, V. Murali Bhaskaran . Analyzing Health Care Dataset using Machine Learning Techniques. International Journal of Computer Applications. 158, 8 ( Jan 2017), 13-15. DOI=10.5120/ijca2017912828

@article{ 10.5120/ijca2017912828,
author = { B. Tamilvanan, V. Murali Bhaskaran },
title = { Analyzing Health Care Dataset using Machine Learning Techniques },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2017 },
volume = { 158 },
number = { 8 },
month = { Jan },
year = { 2017 },
issn = { 0975-8887 },
pages = { 13-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume158/number8/26927-2017912828/ },
doi = { 10.5120/ijca2017912828 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:04:17.330138+05:30
%A B. Tamilvanan
%A V. Murali Bhaskaran
%T Analyzing Health Care Dataset using Machine Learning Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 158
%N 8
%P 13-15
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper mainly deals with different classification algorithms techniques namely Navie Bayes, Sequential Minimal Optimization, Multilayer Perception, and Random Forest. It analyses the breast cancer from UCI machine learning repository. The result of the classification model is precision, recall, F-Measure, time, accuracy. From theses measure, it is observed that naive Bayes algorithms are able to achieve high accuracy and consumed very less time when compare other algorithms.

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Index Terms

Computer Science
Information Sciences

Keywords

Navie Bayes Sequential Minimal Optimization Multilayer Perception Random Forest.

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