Creating turnover risk buckets
Now that you have predicted the probability of turnover for each active employee, you will classify them into different risk bucket as mentioned below:
no-risk
, if 0 <=fit
<= 0.5low-risk
, if 0.5 <fit
<= 0.6medium-risk
, if 0.6 <fit
<= 0.8high-risk
, if 0.8 <fit
<= 1
You will use the cut()
function instead of multiple ifelse()
statements to create the risk buckets.
Risk buckets help you in creating appropriate interventions and retention plans.
This exercise is part of the course
HR Analytics: Predicting Employee Churn in R
Exercise instructions
- Classify the employees in risk buckets based on the
fit
column inemp_risk
as per the conditions mentioned above. - Print the number of employees in each risk bucket.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create turnover risk buckets
emp_risk_bucket <- emp_risk %>%
___(risk_bucket = ___(fit, breaks = c(0, 0.5, 0.6, 0.8, 1),
labels = c("no-risk", "low-risk",
"medium-risk", "high-risk")))
# Count employees in each risk bucket
emp_risk_bucket %>%
___(risk_bucket)