Machine Learning Algorithms for solving Generic Real Life Problems – A Comparative Study

Alt Text: Machine Learning Algorithms for Solving Generic Real-Life Problems – A Comparative Study
Title: Machine Learning Algorithms for Solving Generic Real-Life Problems – A Comparative Study
Caption: A comparative study of various machine learning algorithms for decision-making and data handling.
Description: This research examines multiple machine learning algorithms, including SVM, KNN, Naïve Bayes, Decision Tree, and Neural Networks, comparing their effectiveness in handling real-world problems, missing data, and outlier detection.
Keywords: ML algorithms, SVM, Naïve Bayes, Decision Tree, KNN, Neural Network, Linear Regression

International Journal of Engineering and Techniques – Volume 10 Issue 4, August 2024

Sandeepa Oraon1, Samreen Anjum2, Suman Kumari3, Siba Mitra4
1Student, CSE Dept., Birla Institute of Technology, Mesra, Lalpur. Email: sandeepa2004oraon@gmail.com
2Student, CSE Dept., Birla Institute of Technology, Mesra, Lalpur. Email: samreenanj2@gmail.com
3Student, CSE Dept., Birla Institute of Technology, Mesra, Lalpur. Email: sinhasuman0305@gmail.com
4Assistant Professor, CSE Dept., Birla Institute of Technology, Mesra, Lalpur. Email: sibamitra@bitmesra.ac.in
*Corresponding author

Abstract

Technological advancements have increasingly relied on machine learning to optimize human decision-making. This study provides a comprehensive theoretical analysis of multiple machine learning algorithms, including SVM, KNN, Naïve Bayes, Decision Tree, and Neural Networks. The research evaluates these algorithms based on functionality, handling large datasets, dealing with missing values, overfitting, and outlier detection. Additionally, a comparative study highlights how different algorithms process continuous and discrete data.

Keywords

ML algorithms, SVM, Naïve Bayes, Decision Tree, KNN, Neural Network, Linear Regression

How to Cite

Sandeepa Oraon, Samreen Anjum, Suman Kumari, Siba Mitra, “Machine Learning Algorithms for Solving Generic Real-Life Problems – A Comparative Study,” International Journal of Engineering and Techniques, Volume 10, Issue 4, 2024. ISSN 2395-1303.

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Tags: machine learning research, algorithm comparison, SVM vs decision tree, AI-powered analytics, peer-reviewed journal, indexed research publication.

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