Mathematical Problems in Engineering / 2019 / Article / Tab 2

Research Article

An Improved Random Forest Algorithm for Predicting Employee Turnover

Table 2

Value ranges of 32 features.

No.FeatureValue Range

1Attrition (class name)Yes, No
2EmployeeNumber0~2000
3Age22~60
4GenderFemale, Male
5EmploymentNatureRegular Worker, Dispatched Worker
6JobLevel(high) 4~13 (low)
7JobRoleStaff, Junior Management, Middle Management, Senior Management
8MonthlyIncome5000~97938
9DepartmentTypeSales, Management, Technical
10DistanceFromHome1~20
11EducationAcademy, Bachelor, Master, Doctor
12EducationFieldTechnology, Management, Economics, Other
13RelationshipSatisfactionLow, Medium, High, Very High
14WorkLifeBalanceBad, Good
15EnvironmentSatisfactionLow, Medium, High, Very High
16JobSatisfactionLow, Medium, High, Very High
17OverTimeYes, No
18AvgWorkHours8~16
19MaritalStatusYes, No
20HaveChildrenYes, No
21NumberCompaniesWorked0~3
22TotalWorkingYears0~37
23YearsatCompany0~36
24YearsinCurrentRole0~14
25YearswithCurrentManager0~12
26WinningCount0~5
27PerformanceRatingLastYearLow, Good, Excellent, Outstanding
28PercentSalaryIncrease0~30
29YearsSinceLastPromotion0~32
30TrainingTimesLastYear0~5
31NativePlaceLocal, Nonlocal
32PhysicalConditionHealthy, Unhealthy

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