Projects done as a part of class work
In any Organization recruting a person Involves lot of time and money. After lot of efforts we recruit a person and he /she don't join the Organization it leads to lot of loss. The main objective of this model is to predict whether the person will join or not.
The dataset contains 17 variables and 12,333 records.
- Candidate Ref -- numeric variable
- DOJ Extended -- categorical variable.It contains two categories as YES and NO
- Duration to accept offer -- Numeric Variable
- Notice period -- numeric variable
- Offered band -- categorical variable. It has 7 categories from 'E0' to 'E6'
- Pecent.hike.expected.in.CTC -- numeric variable
- Percent.hike.offered.in.CTC -- numeric variable
- Percent.difference.CTC -- numeric variable
- Joining.Bonus -- categorical variable.It contains two categories as YES and NO
- Candidate.relocate.actual -- categorical variable.It contains two categories as YES and NO
- Gender -- categorical variable.It contains two categories as MALE and FEMALE
- Candidate.Source -- categorical variable with 3 categories as 'Agency', 'Direct' and 'Employee Referral'
- Rex.in.Yrs -- numeric variable
- LOB(Location of boarding) -- categorical variable with 12 categories.
- Location -- categorical variable with 12 categories.
- Age -- numeric variable
- Status -- categorical variable.It contains two categories as JOINED and NOT JOINED