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I would like to find how to change my data structure to make it compatible with a ML model, with the following constraints :

  • A Product is defined by {id, price, continuousVariable1, ..., continuousVariable10}
  • The training set is train.csv. Each line contains a date, a Product, and a list of Products (competing products)
  • For each row of train.csv, the size of the list of Products may change.

It would be easy if I had only one competing products : I could put all columns in the same file. But I have many competing products. The output variable is the product price.

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I my opinion, the best way is if you create a column for every(!) product. Yes, u will get a high dimensional sparse Matrix but it should solve you problem quickly.

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