|
|||||||||||||||
|
INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, 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) |
||||||||||||||
Issue: May 2024
Volume 9 | Issue 5
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.76
Issue per Year : 12
Volume Published : 9
Issue Published : 96
Article Submitted :
Article Published :
Total Authors :
Total Reviewer :
Total Countries :
Indexing Partner
Join RMS/Earn 300
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | A Comparative Analysis of Customer Churn Prediction Models in Python Using Scikit-Learn |
| Authors Name: | Jaipreet Singh , Gurvir Singh Sidhu , Inderjeet Singh , Prabhneet Singh |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_208087
|
| Published Paper Id: | IJNRD2311190 |
| Published In: | Volume 8 Issue 11, November-2023 |
| DOI: | |
| Abstract: | In the sector of big-scale groups, the problem of consumer churn has grown into a powerful assignment. As an end result, corporations are actively searching for progressive methods to predict capability patron churn quotes. It has turn out to be imperative to discover the factors that contribute to elevated purchaser churn prices, allowing organizations to take the essential steps to mitigate this phenomenon. The primary objective of our group's efforts is to craft a robust churn prediction model which could help companies in pinpointing clients at the highest chance of churning. To gauge the version's performance, we hired the broadly common Area Under the Curve (AUC) measurement, which gives a dependable measure of predictive accuracy. Impressively, the AUC price we carried out became 84.93%, signifying the effectiveness of our version. To execute our study, we hired the flexible and available platform of Google Colab. The dataset we used is the Teleco Churn Dataset, simply to be had on Kaggle, an open-source platform that provides a wealth of dataset assets to the general public. This dataset offers a complete compilation of consumer statistics spanning an extended length, serving as the foundational statistics for schooling, checking out, and evaluating our churn prediction gadget. Our version underwent a rigorous trying out system, with an assessment of its performance throughout ten distinct algorithms: Decision Tree, Random Forest, Gradient Boost, Logistic Regression, Adaboost, SVC, Gaussian Naïve Bayes, Kernel Support Vector Machine, K Nearest Neighbour and Voting Classifier. However, the best results are obtained by applying the Voting Classifier algorithm. |
| Keywords: | |
| Cite Article: | "A Comparative Analysis of Customer Churn Prediction Models in Python Using Scikit-Learn", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 11, page no.b706-b710, November-2023, Available :http://www.ijnrd.org/papers/IJNRD2311190.pdf |
| Downloads: | 000118750 |
| 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 |
| Publication Details: |
Published Paper ID:IJNRD2311190 Registration ID: 208087 Published In: Volume 8 Issue 11, November-2023 DOI (Digital Object Identifier): Page No: b706-b710 Country: Mohali, Punjab, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2311190 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2311190 |
| Share Article: |
|
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijnrd.org
| Semantic Scholar | Microsaoft Academic | ORCID | Zenodo |
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | PUBLON |
| DRJI | SSRN | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Social Media
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Join RMS/Earn 300
| Copyright © 2024 - All Rights Reserved - IJNRD |
Facebook Twitter Instagram LinkedIn