UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
Call for Paper
Volume 11 | Issue 3 | March 2024

JETIREXPLORE- Search Thousands of research papers



WhatsApp Contact
Click Here

Published in:

Volume 8 Issue 3
March-2021
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

Unique Identifier

Published Paper ID:
JETIR2103320


Registration ID:
307248

Page Number

2563-2569

Share This Article


Jetir RMS

Title

Providing an efficient Customers Churn Prediction Model based on Improvised K-Means Clustering And Non Linear Support Vector Machine

Abstract

This paper proposed a new approach to enhance the performance of existing base techniques including Neural networks, Logistic Regression, Linear Support vector machines and Non-Linear support vector machine with the proposed technique Improvised K-Means with NLSVM. The Improvised K-Means algorithm resolved the random selection problem of cluster centroid of K-Means by choosing the cluster centroid by taking the mean value of the data points. The Improvised K-Means algorithm clusters are then classified with Non-Linear Support vector machine classification algorithm. This enhanced approach is used for predicting customer churn. So that proactive measures could be taken by company for churn prevention. The experimental results show that the proposed technique performs better than the existing base techniques in terms of recall and f-measure.

Key Words

Data Mining, Customer Churn Prediction, Clustering, Classification, K-Means, Non-Linear Support Vector Machine (NLSVM).

Cite This Article

"Providing an efficient Customers Churn Prediction Model based on Improvised K-Means Clustering And Non Linear Support Vector Machine", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 3, page no.2563-2569, March-2021, Available :http://www.jetir.org/papers/JETIR2103320.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Providing an efficient Customers Churn Prediction Model based on Improvised K-Means Clustering And Non Linear Support Vector Machine", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 3, page no. pp2563-2569, March-2021, Available at : http://www.jetir.org/papers/JETIR2103320.pdf

Publication Details

Published Paper ID: JETIR2103320
Registration ID: 307248
Published In: Volume 8 | Issue 3 | Year March-2021
DOI (Digital Object Identifier):
Page No: 2563-2569
Country: Jalandhar, Punjab, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


Preview This Article


Downlaod

Click here for Article Preview

Download PDF

Downloads

0002969

Print This Page

Current Call For Paper

Jetir RMS