Input data with each cell containing an array instead of a single numerical or categorical entry.
Urgent!! I have posted this before under a different caption but have not received any response. I am trying to build a model which must take in all inputs as arrays. (Each cell would consist of arrays of the same size). The numerical inputs have to be arrays and the categorical ones also have to be arrays. The reason is that the predicted output is provided as a "group" but there are several members in each group which have separate decision variables. . Each member contributes to the group output in different ways depending on its decision variables. Imagine for example that I have 1000 football matches as sample data and would like to predict the number of goals that will be scored by a team from that dataset. I know that the number of goals is based on team work and each player contributes to the goal. So I get the decision variable for each team player such as (age, skill level, experience, role etc), but my predicted output (number of goals) is a 'group value' so I cant assign an output for each player rather I can only assign an output for each team, but I need to be able to individually provide the input variables for each and all players (array) of that team in each cell. How is this kind of problem solved in rapidminer?