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Emperical Evaluation of Machine Learning algorithms for Breast Cancer Data Classification

S. Kumaravel1 , S. Ophilia Domanica Vithya2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-10 , Page no. 346-351, Oct-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i10.346351

Online published on Oct 31, 2018

Copyright © S. Kumaravel, S. Ophilia Domanica Vithya . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S. Kumaravel, S. Ophilia Domanica Vithya, “Emperical Evaluation of Machine Learning algorithms for Breast Cancer Data Classification,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.346-351, 2018.

MLA Style Citation: S. Kumaravel, S. Ophilia Domanica Vithya "Emperical Evaluation of Machine Learning algorithms for Breast Cancer Data Classification." International Journal of Computer Sciences and Engineering 6.10 (2018): 346-351.

APA Style Citation: S. Kumaravel, S. Ophilia Domanica Vithya, (2018). Emperical Evaluation of Machine Learning algorithms for Breast Cancer Data Classification. International Journal of Computer Sciences and Engineering, 6(10), 346-351.

BibTex Style Citation:
@article{Kumaravel_2018,
author = {S. Kumaravel, S. Ophilia Domanica Vithya},
title = {Emperical Evaluation of Machine Learning algorithms for Breast Cancer Data Classification},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2018},
volume = {6},
Issue = {10},
month = {10},
year = {2018},
issn = {2347-2693},
pages = {346-351},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3029},
doi = {https://doi.org/10.26438/ijcse/v6i10.346351}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i10.346351}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3029
TI - Emperical Evaluation of Machine Learning algorithms for Breast Cancer Data Classification
T2 - International Journal of Computer Sciences and Engineering
AU - S. Kumaravel, S. Ophilia Domanica Vithya
PY - 2018
DA - 2018/10/31
PB - IJCSE, Indore, INDIA
SP - 346-351
IS - 10
VL - 6
SN - 2347-2693
ER -

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Abstract

Breast cancer (BC) is a deathly cancer disease which occurs mainly in women and the greater number of breast cancer patients leads to death according to global statistics. The early examination of Breast Cancer can augment the durability of patients, and it helps to improve the prompt medication to the patients. Machine learning plays an important role in health care and they are more powerful in classification and prediction process. There are various classification algorithms used based upon then data set. This work is the implementation of few classification algorithms such as Random Forest, K Nearest Neighbor, Navie Bayes, Support Vector Machine, and Artificial Neural Network for breast cancer data set. This paper is the comparative study of these algorithms using R tool. The goal of this paper is to analyze the accuracy of these algorithms. The implementation procedure reveal that the performance of any algorithm varies based on the data set attributes and characteristics.

Key-Words / Index Term

Machine Learning, Classification, Random Forest, K Nearest Neighbor, Navie Bayes, Support Vector Machine, Artificial Neural Network, R Tool

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