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HRアナリティクス:Rで社員離職を予測する
中級スキルレベル
更新日 2024/08RMachine Learning4時間14 ビデオ50 演習4,000 XP4,834達成証明書
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HR Analytics: Exploring Employee Data in R1
Introduction
This chapter begins with a general introduction to employee churn/turnover and reasons for turnover as shared by employees. You will learn how to calculate turnover rate and explore turnover rate across different dimensions. You will also identify talent segments for your analysis and bring together relevant data from multiple HR data sources to derive more useful insights.
2
Feature Engineering
In this chapter, you will create new variables from existing data to explain employee turnover. You will analyze compensation data and create compa-ratio to measure pay equity of all employees. To identify the most important variables influencing turnover, you will use the concept of Information Value (IV).
3
Predicting Turnover
In this chapter, you will build a logistic regression model to predict turnover by taking into account multicollinearity among variables.
4
Model Validation, HR Interventions, and ROI
In this chapter, you will calculate the accuracy of your model and categorize employees into specific risk buckets. You will then formulate an intervention strategy and calculate the ROI for this strategy.
HRアナリティクス:Rで社員離職を予測する
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