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 <= 0.5
low-risk, if 0.5 < fit <= 0.6
medium-risk, if 0.6 < fit <= 0.8
high-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.

Cet exercice fait partie du cours

HR Analytics: Predicting Employee Churn in R

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Instructions

Classify the employees in risk buckets based on the fit column in emp_risk as per the conditions mentioned above.
Print the number of employees in each risk bucket.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de 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)

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