Paper Title

Analysis of Machine Learning Algorithm: SMOTE with SVM

Article Identifiers

Registration ID: IJNRD_192654

Published ID: IJNRD2304631

DOI: Click Here to Get

Authors

Pallavi Ahirwar , ANJNA JAYANT DEEN , MANISH KUMAR AHIRWAR

Keywords

SMOTE, SVM, majority class, minority class, imbalanced data, lung cancer data.

Abstract

Imbalanced datasets are common in many real-world applications, such as fraud detection, disease diagnosis, and anomaly detection, where the occurrence of the target event is rare or infrequent. In general machine learning algorithms are prone to classify for majority class. In dealing with imbalanced class datasets various problems occur, however, the majority class samples can be leading to a misleading impression of accuracy and desired target. In handling such a situation that can use by many researchers is SMOTE (Synthetic Minority Over-sampling Technique), which creates synthetic samples for the minority class and resolves the over-fitting problem caused by random over-sampling of the majority class. This study thoroughly investigated SMOTE to discover the noteworthy outcomes of classification algorithms for imbalanced datasets. This creates an oversampled dataset for minority class to try to reduce over fitting and unbefitting problems of class imbalance; and creates more balanced dataset for training in classification models. In this study SMOTE can be used with various classification algorithms, such as KNN, Decision trees, Random forests, and Support vector machine for analysis and betterments of classification algorithms.

How To Cite

"Analysis of Machine Learning Algorithm: SMOTE with SVM", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 4, page no.g256-g264, April-2023, Available :https://ijnrd.org/papers/IJNRD2304631.pdf

Issue

Volume 8 Issue 4, April-2023

Pages : g256-g264

Other Publication Details

Paper Reg. ID: IJNRD_192654

Published Paper Id: IJNRD2304631

Downloads: 000121216

Research Area: Computer Science & Technology 

Country: Bhopal, Madhya Pradesh , India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2304631.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2304631

About Publisher

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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Call For Paper - Volume 10 | Issue 8 | August 2025

IJNRD is Scholarly open access journals, Peer-reviewed, and Refereed Journals, High Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool), Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) with Open-Access Publications.

INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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Current Issue: Volume 10 | Issue 8

Last Date for Paper Submission: Till 31-Aug-2025

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