HR Analytics: Predicting Employee Churn in R
Abhishek Trehan
People Analytics Practitioner
$$ IV = (\sum \text{(\% of non-events - \% of events)}) * \log(\frac{\text{\% of non-events}}{\text{\% of events}}) $$
# Load Information package
library(Information)
# Compute Information Value
IV <- create_infotables(data = emp_final, y = "turnover")
# Print Information Value
IV$Summary
Variable IV
12 percent_hike 1.144784e+00
17 total_dependents 1.088645e+00
21 no_leaves_taken 9.404533e-01
31 tenure 9.332570e-01
27 mgr_effectiveness 6.830020e-01
11 compensation 6.074885e-01
| Informační hodnota | Prediktivní síla |
|---|---|
| < 0.15 | Slabá |
| Mezi 0.15 a 0.4 | Střední |
| > 0.4 | Silná |
percent_hike: 1.14 (Silná)compa_ratio: 0.29 (Střední)HR Analytics: Predicting Employee Churn in R