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A Deep Analysis and Efficient Implementation of Supervised Machine Learning Algorithms for Enhancing The Classification Ability of System

Sandeep Kumar Verma1 , Turendar Sahu2 , Manjit Jaiswal3

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-3 , Page no. 1094-1101, Mar-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i3.10941101

Online published on Mar 31, 2019

Copyright © Sandeep Kumar Verma, Turendar Sahu, Manjit Jaiswal . 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: Sandeep Kumar Verma, Turendar Sahu, Manjit Jaiswal, “A Deep Analysis and Efficient Implementation of Supervised Machine Learning Algorithms for Enhancing The Classification Ability of System,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.1094-1101, 2019.

MLA Style Citation: Sandeep Kumar Verma, Turendar Sahu, Manjit Jaiswal "A Deep Analysis and Efficient Implementation of Supervised Machine Learning Algorithms for Enhancing The Classification Ability of System." International Journal of Computer Sciences and Engineering 7.3 (2019): 1094-1101.

APA Style Citation: Sandeep Kumar Verma, Turendar Sahu, Manjit Jaiswal, (2019). A Deep Analysis and Efficient Implementation of Supervised Machine Learning Algorithms for Enhancing The Classification Ability of System. International Journal of Computer Sciences and Engineering, 7(3), 1094-1101.

BibTex Style Citation:
@article{Verma_2019,
author = {Sandeep Kumar Verma, Turendar Sahu, Manjit Jaiswal},
title = {A Deep Analysis and Efficient Implementation of Supervised Machine Learning Algorithms for Enhancing The Classification Ability of System},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2019},
volume = {7},
Issue = {3},
month = {3},
year = {2019},
issn = {2347-2693},
pages = {1094-1101},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3972},
doi = {https://doi.org/10.26438/ijcse/v7i3.10941101}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i3.10941101}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3972
TI - A Deep Analysis and Efficient Implementation of Supervised Machine Learning Algorithms for Enhancing The Classification Ability of System
T2 - International Journal of Computer Sciences and Engineering
AU - Sandeep Kumar Verma, Turendar Sahu, Manjit Jaiswal
PY - 2019
DA - 2019/03/31
PB - IJCSE, Indore, INDIA
SP - 1094-1101
IS - 3
VL - 7
SN - 2347-2693
ER -

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Abstract

Machine Learning, a subset of Artificial Intelligence is very popular and emerging field of science which basically focus on designing the approach enabling the computer or machines to learn from the input provided or past experience. There are lots of application of Machine Learning in day-to-day life such as face detection and recognition, decision making in business forecasting, etc. It is also becoming the business subject to various giant enterprises like Amazon, Google, FaceBook, etc. In this paper, we have focused our discussion to some popular Supervised Machine Learning algorithms that are SVM, logistic regression, Multinomial Naive Bayes, KNN apart from some other supervised Machine Learning algorithms like Linear Regression, Linear Discriminant Analysis, Decision Tree, Random Forest, Naïve Bayes, etc. and we determine the most efficient classification algorithm based on the data set which is multiclass dataset. This research paper gives some clarity to the selection of algorithm specific to some application. And we have shown the comparative results.

Key-Words / Index Term

Machine Learning (ML), K-nearest neighbours (KNN), Logistic Regression (Log), Multinomial Naïve Bayes (MulNB), Support Vector Machine (SVM), Classifier

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