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A Probabilistic Machine Learning Approach for Eligible Candidate Selection

by Marium-E-Jannat, Sayma Sultana Chowdhury, Munira Akther
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 144 - Number 10
Year of Publication: 2016
Authors: Marium-E-Jannat, Sayma Sultana Chowdhury, Munira Akther
10.5120/ijca2016910439

Marium-E-Jannat, Sayma Sultana Chowdhury, Munira Akther . A Probabilistic Machine Learning Approach for Eligible Candidate Selection. International Journal of Computer Applications. 144, 10 ( Jun 2016), 1-4. DOI=10.5120/ijca2016910439

@article{ 10.5120/ijca2016910439,
author = { Marium-E-Jannat, Sayma Sultana Chowdhury, Munira Akther },
title = { A Probabilistic Machine Learning Approach for Eligible Candidate Selection },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2016 },
volume = { 144 },
number = { 10 },
month = { Jun },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume144/number10/25212-2016910439/ },
doi = { 10.5120/ijca2016910439 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:47:14.850450+05:30
%A Marium-E-Jannat
%A Sayma Sultana Chowdhury
%A Munira Akther
%T A Probabilistic Machine Learning Approach for Eligible Candidate Selection
%J International Journal of Computer Applications
%@ 0975-8887
%V 144
%N 10
%P 1-4
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Now-a-days Machine learning approach is used to solve many problems where intelligence is involved. Lots of time consuming task are done by computers with the power of statistics. In this paper, a machine learning based candidate selection procedure is proposed and implemented for a particular field. A huge amount of activity is involved in the job recruitment procedure. To reduce the manual task a probabilistic machine learning approach is described in this paper. A popular machine learning approach named Naive Bayes Classifier is used to implement the method. Baseline criteria selection depends on the recruiters demand. The proposed system learns from training dataset and produces a short listed eligible list based on learning. The more perfectly one feed the system result will be more accurate.

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Index Terms

Computer Science
Information Sciences

Keywords

Machine Learning Probability Statistics Naive Bayes Classifier.

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