Im am interested in solving the task from the data mining cup 17 for an online-shop.It is simliar to the the kaggle competition of Romann. You have user IDs, and product attributes like the price of the competitor. Plus those attributes you have the information if the user X clicked, or even ordered the product or only assigned the product to the shopping basket.My response variable is the revenue of purchased product. So if only click on a product it gives no revenue of course.So, I would solve this task with a random forest If you have only the product features to classify revenue.But, of course the time history of how often e.g. a product is clicked in the last 5 days or assigned to the basket will influences the likelihood og beeing purchased.How I use such an time history together with a random forest forecasting?So I have a interaction between the product features and a time dependent user interaction which might influences revenue.I would be pleased about logical advices how I have to perform such an task
Revenue forecast with user dependent actions
machine learning;random forest