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.

本练习是课程的一部分

HR Analytics: Predicting Employee Churn in R

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练习说明

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.

交互式实操练习

通过完成这段示例代码来试试这个练习。

# 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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