Mobile users view a brochure from a retailer published on our platforms. Each time a brochure is viewed, we capture several data associated with the user, i.e., how the user engages with the content. Given the datasets below, predict which user is still active in July based on the behavior of April until June. How would you approach that problem? What other data points would increase the accuracy of the algorithm? Which features did you select and why?
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