Study on Class Imbalance Problem with Modified KNN for Classification

R. Sasirekha, B. Kanisha, S. Kaliraj

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

Identification of data imbalance is a very challenging one in the modern era. When we go for a data warehouse, there would be a vast data available in it but managing data and sustaining the balanced state of data is very difficult to handle in any type of sector. Occurrence of data imbalance comes when specimens are classified based on their behaviour. In this paper, the imbalance state of data is analysed and the machine learning techniques are studied carefully to choose the best technique to handle data imbalance problems. Wide analysis of the k-nearest neighbour (KNN) algorithm can be carried out to keep the classification of specimens grouped equally.

Original languageEnglish
Title of host publicationLecture Notes on Data Engineering and Communications Technologies
PublisherSpringer Science and Business Media Deutschland GmbH
Pages207-217
Number of pages11
DOIs
Publication statusPublished - 2022

Publication series

NameLecture Notes on Data Engineering and Communications Technologies
Volume101
ISSN (Print)2367-4512
ISSN (Electronic)2367-4520

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Media Technology
  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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