Setting up the target variable in a classification problem

@Ayan_dbpc wrote:

Hi -
Currently I’m working on a human resources project where I need to predict attrition.
I have the active list of employees as on Sep’17 and the list of churned employees for different years starting 2012. I need to predict which employees will leave from Oct’17 to Mar’18.

My approach has been:

1. Tag all active employees as on Sep’17 as active
2. Tag all churned employees in 2017 as inactive
3. Split data into train and validation
4. Build model and check performance

Is this approach correct? Are there any other alternative approaches in predicting employee churn?

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