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I have a set of features as follows:

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Where gift is categorical features and value of gift is value of the gift (numerical features). Both are the promotion. The objective is that I would like to forecast the sale for next day (or week).

My idea is embedding gift and value of gift into one vector (I call: Promotional characteristics), then It will be the new feature. I will use this features and sale to forecast.

Will my idea be correct and if possible, what is the technique to embedding gift and value of gift into one vectors?

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  • $\begingroup$ Is your problem here only to deal with Categorical variable (Gift) and transform it to Numerical so you can use a model with it ? If so, depending on the number of possible values, you can use One Hot Encoder or Categorical Encoder. You should check this answer : datascience.stackexchange.com/a/97949/101580 $\endgroup$
    – Adept
    Aug 5, 2021 at 6:40
  • $\begingroup$ Yes, I would like to deal with both Categorical variable! One hot encoder is the good method. But beside the variable of gift, there are also other feature such as weekday of the promotion. I would like to embed all thing relate to promotion (gift, value, day of promotion) into 1 vector! Correct me if my idea be wrong! $\endgroup$
    – Sherry
    Aug 5, 2021 at 6:51
  • $\begingroup$ What do you mean by one vector ? You have to keep 1 line per index (here, 1 line per day), but yoi can multiply variables with OneHot (if there's not too much) $\endgroup$
    – Adept
    Aug 5, 2021 at 7:09
  • $\begingroup$ One vector mean I would like to find a vector represent for gift variable (include gift, value of gift,...) $\endgroup$
    – Sherry
    Aug 5, 2021 at 7:12
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    $\begingroup$ I understood your instructions! Many thanks! But it case gifl columns have lot of elements, what will be the method to replace OneHot $\endgroup$
    – Sherry
    Aug 5, 2021 at 7:49

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