Interview Query

Chronological Order in Boosting

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Have you seen this question before?

Let’s say you’re analyzing a Netflix users dataset that was collected over a period of 10 years.

You are training a boosting algorithm on the data to predict whether a user will trust the website, indicated by them entering their credit card info for a trial period.

When training your model, would it be a good idea to separate the user groups based on the year they became a Netflix member? Why or why not?

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