Efficient project management by Employee Over-Time prediction
A manufacturing unit is consistently facing project over-time to finish. This is usually a sign for poor project planning or resource allocation. Now the company has decided smartly allocate the resource based on ML models. One indicator they have about project going out-of-budget is number of employees working overtime. If a good predictive model can help them predict which employees are expected to do overtime, then they can balance the resource allocation accordingly. Your job is to build a Machine Learning model which will predict whether an employee will bill overtime on a project or not. Evaluation Metric: If Accuracy>65 then give the score for Recall Datasets: You have been provided MiTHDataset.csv which contains both train and test samples. A sample can be treated as train sample If istrain=1 otherwise it is treated as test sample. Train samples has Target value , whereas test samples does not have Target value. It was kept as NA. You need to predict Target for the test samples and upload your predictions in the samplesubmission.csv format.
Attributes: S.NO Attribute 1 Age 2 Frequencyof_Travel 3 DailyRate 4 Division 5 DistancetoOffice 6 Education 7 Specialization 8 No.of Employees 9 EmployeeID 10 OfficeAmbianceRating 11 Gender 12 HourlyRate 13 SelfMotivated 14 JobLevel 15 Designation 16 Happynesslevel in job 17 MaritalStatus 18 SalaryperMonth 19 MonthlyRate 20 NumberofCompaniesChanged 21 Over18 22 Working Extratime(Target) 23 PercentSalaryHike 24 PerformanceRating 25 RelationshipSatisfaction 26 StandardHours 27 ESOPs(stackoptions) 28 DateOnwhich_datacollected 29 NoofTrainings_Attended 30 WorkLifeBalance 31 DateOfjoininginthe_CurrentCompany 32 No of years with current designation 33 YearsSinceLastPromotion 34 YearsWithCurrManager 35 Istrain- (1 train sample,0 test sample) 36 NoofTrainings_Attended 37 WorkLifeBalance