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BayesÂ’ Approach on Government Job Selection Procedure In India

 SONU RANA1 and Dr. ABHOY CHAND MONDAL2 Assistant Professor, Department of CSE, Aryabhatta Institute of Engineering & Management Durgapur Panagarh, Dist Burdwan, India Associate Professor, Department of CSE, The University Of Burdwan, Dist-Burdwan, West Bengal, India Related article at Pubmed, Scholar Google

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Abstract

In this paper, we have discussed Government Job Selection procedure in India through Bayes’ theorem, or the related likelihood ratio, is the key to almost any procedure for extracting information from data. Bayes’ Theorem lets us work backward from measured results to deduce what might have caused them. It will be the basis of most of our later model building and testing .

Keywords

Bayes’ Theorem, Strength, Certainty, and Coverage Factor, Flow graph.

I . INDTRODUCTION OF BAYES’ THEOREM

Bayes’ Theorem, or the related likelihood ratio, is the key to almost any procedure for extracting information from data. Bayes’ Theorem lets us work backward from measured results to deducewhat might have caused them. It will be the basis of most of our later model building and testing. It UCalgary (2003) is the work of Rev. Thomas Bayes (St.Andrews, 2003), about whom only a modest amount is known, but he has the perhaps unique distinction that twothirds of his publications were posthumous and the remaining third anonymous.
Every decision table describes decisions (actions, results etc.) determined, when some conditions are satisfied. In other words each row of the decision table specifies a decision rule which determines decisions in terms of conditions. In  II . RELATED WORK

In this article we will illustrate an idea which is based on Government job selection in India. Here, we have taken 1000 examination candidates (X1,X2,…..,X11) who are preparing them for government job examination in India. For some government rules each candidate have to fulfil each condition or criteria for getting government job in India. These conditions are K=Knowledge/ Intelligence, C=Cast, D= Degree, M=Percentage of marks, E= exam Rank. If each criteria is satisfy then candidate will selected for government job. In Table one the value of each criteria based on Md= Medium, Gd= Good, Vgd= Verygood , ST= Schedule Tribe, SC= Schedule Cast, Gen= General, Hnd=Physical Handicap, OBC= Other Backward Cast, Passed and Fail.

III . DECISION ALGORITHM ASSOCIATED WITH RESPECT OF TABLE 1

X1)if (k=Md, C= ST, D=Md, M= Md, E=Pass) then (Decision is Selected)
X2) if (k=Md, C= Gen, D=Md, M=Md, E=Fail) then (Decision is Rejected)
X3) if (k=Gd, C= SC, D=Gd, M=,Gd, E=Pass) then (Decision is Selected)
X4)if (k=Md, C= Gen, D=Gd, M= Gd, E=Fail)then (Decision is Rejected)
X5)if (k=Vgd, C= Gen, D=Vgd, M=Vgd, E=Pass) then (Decision is Selected)
X6)if (k=Md, C= Gen, D=Vgd, M= Gd, E=Fail) then (Decision is Rejected)
X7)if (k=Vgd, C= Gen, M=Vgd, E=Pass) then (Decision is Selected)
X8)if (k=Vgd, C= ST/SC, E=Pass) then (Decision is Selected)
X9)if (k=Md, C= Hnd, E=Pass) then (Decision is Selected)
X10)if (k=Gd, C= OBC, D=Gd, M=Gd, E=Fail) then (Decision is Rejected)
X11)if (k=Gd, C= OBC, D=Vgd, M=Vgd, E=Pass) then (Decision is Selected)
Now Let Calculate The Inverse Decision Algorithm in below:
X1’)if(Decision is Selected) then (k=Md, C= ST, D=Md, M= Md, E=Pass).
X2’) if (Decision is Rejected) then (k=Md, C= Gen, D=Md, M= Md, E=Fail)
X3’) if (Decision is Selected) then(k=Gd, C= SC, D=Gd, M=,Gd, E=Pass)
X4’)if(Decision is Rejected) then (k=Md, C= Gen, D=Gd, M= Gd, E=Fail)
X5’)if(Decision is Selected) then (k=Vgd, C= Gen, D=Vgd, M=Vgd, E=Pass)
X6’)if (Decision is Rejected) then (k=Md, C= Gen, D=Vgd, M= Gd, E=Fail)
X7’)if(Decision is Selected) then (k=Vgd, C= Gen, M=Vgd, E=Pass)
X8’)if(Decision is Selected) then (k=Vgd, C= ST/SC, E=Pass)
X9’)if(Decision is Selected) then (k=Md, C= Hnd, E=Pass)
X10’)if(Decision is Rejected) then ( k=Gd, C= OBC, D=Gd, M=Gd, E=Fail)
X11’)if(Decision is Selected) then (k=Gd, C= OBC, D=Vgd, M=Vgd, E=Pass)

CONCLUSION

In this paper, from above discussion we can reach ultimate solution that for getting Government job in India some criteria are most important to qualify the examination test. With respect of some important criteria we got “X6, X10,X7,X9” are eligible to clear the exam test but X2,X5,X11,X4 these candidates are not properly eligible to clear the exam for getting the job and those we are succeed to achieve the goal through Bayes’ Theorem which actually expertism evolutionary method which help to reach actual decision.

Tables at a glance    Table 1 Table 2 Table 3 Table 4

Figures at a glance Figure 1