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ISSN:- 2349-3585

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Optimal Stopping Algorithm for Modern Interview Process using Machine Learning
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Author's Name: Ishwari Sawant,Govind Kshirsagar,Monika Jagtap,Vai,,,

AuthorsAbstractReferencesKeywords

Authors: Ishwari Sawant,Govind Kshirsagar,Monika Jagtap,Vai,,,
Branch: Computer engineering
Volume: VOLUME - 15
Album: Issue-6,June-2021

Abstract—This Research Paper Aims to Provide the Balance of Time and Quality in modern interview process using Optimal Stopping Algorithms coupled with machine learning algorithm called as decision tree classifier. In Any optimal stopping problem, the crucial dilemma is not which option to pick, but how many options to even consider. We try to answer this question by combining optimal stopping algorithm and machine learning with human intuition.

Keywords: Optimal stopping algorithm, Decision Tree Classifier, 37% rule, Interview Process.

[1] Brian Christianand Tom Griffiths, “AlgorithmstoLiveBy: The Computer Science of Human Decisions”, ISBN9781250118363

[2] Zishuo Zhao, “An Asymptotic Analysis on Generalized Secretary Problem”, ComputerScienceandGameTheory (cs.GT), 16Sep2019

[3] Thomas S. Ferguson, “Who Solved the Secretary Problem?”, StatisticalScience, Vol. 4, No. 3 (Aug.,1989), pp. 282-289

[4] Hill, TheodoreP. “Knowing Whento Stop: How to Gamble If You Must—the Mathematics of Optimal Stopping.” American Scientist, vol. 97, no. 2, 2009, pp.126–133