ML Assignment – HR CHURN PREDICTION Guidelines: i. This Assignment is mandatory for everyone. ii. It is mandatory to submit the answer with the screen shot of the output you have received. Otherwise, no marks will be given. iii. If anyone fails to submit the assignment within the last date. His/her assignment submission will not be evaluated and will be allotted minus marks also. Case study: There is an ever increase in focus of effective requirement. An organization invest a lot of time and resources in search of potential candidates. The investment become loses is the selected candidate do not join organization in the end. Challenges: ➢ Recruiter need to understand the chances of candidate of joining the organization. ➢ There are numerous factors for which the candidate can backout of the job. ➢ Confidential data cannot be obtained. Research: The variables collected were as follows:
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Candidate reference number Unique number to identify the candidate
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DOJ extended Binary variable identifying whether candidate asked for date of joining extension (Yes/No)
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Duration to accept the offer Number of days taken by the candidate to accept the offer (continuous variable)
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Notice period Notice period to be served in the parting company before candidate can join this company (continuous variable)
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Offered band Band offered to the candidate based on experience and performance in interview rounds (categorical variable labelled C0/C1/C2)
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Percentage hike expected Percentage hike expected by the candidate (continuous variable)
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Percentage hike offered Percentage hike offered by the company (continuous variable)
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Percentage difference Difference of hike offered and hike expected is considered
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Joining bonus Binary variable indicating if joining bonus was given or not (Yes/No)
10.Gender Gender of the candidate (Male/Female)
11.Candidate source Source from which resume of the candidate was obtained (categorical variables with categories: Employee referral/Agency/Direct)
12.Year of experience (in years) Relevant years of experience of the candidate for the position offered (continuous variable)
13.LOB Line of business for which offer was rolled out (categorical variable)
14.DOB Date of birth of the candidate
15.Joining location Company location for which offer was rolled out for candidate to join (categorical variable)
16.Candidate relocation status Binary variable indicating whether candidate has to relocate from one city to another city for joining (Yes/No)
17.HR status Final joining status of candidate (Joined/Not-Joined)
Dataset: Dataset is named as “HR_Data”, It consists of 18 columns and 8998 rows in the datase