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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
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Published Paper Details:
Paper Title
Employee Attrition Using Machine Learning With Reinforcement Algorithm
Authors
Tanmay Jain, Vanshika Pritmani, Varun Agrawal, Aditya Patil, Shuhaab Shafi
Keywords
Employee attrition, Decision tree, machine learning, K-Nearest Neighbors(KNN), Support vector machines(SVM), Random Forest
Abstract
Employee attrition, the phenomenon of employees leaving a company, poses significant challenges for organizations, including loss of talent, increased recruitment costs, and decreased productivity. This paper gives an understanding of employee attrition. The main purpose of this paper is to give maximum accuracy as possible. Which is being done by using Random Forest algorithm. The algorithms such as KNN, decision tree and SVM are used. The main purpose is to show how Random Forest which gives better accuracy than ANN. The data set used is of IBM employee attrition. The accuracy of Random Forest algorithm is 95.74 %. Which is the highest of any other algorithms.
IJCRT's Publication Details
Unique Identification Number - IJCRT2407479
Paper ID - 265835
Page Number(s) - e142-e144
Pubished in - Volume 12 | Issue 7 | July 2024
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Tanmay Jain, Vanshika Pritmani, Varun Agrawal, Aditya Patil, Shuhaab Shafi, "Employee Attrition Using Machine Learning With Reinforcement Algorithm", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 7, pp.e142-e144, July 2024, Available at :http://www.ijcrt.org/papers/IJCRT2407479.pdf
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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