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Let's say I have a data set like the following:

file group_a_co_1 group_a_co_2 group_b_co_1 group_b_co_2 file_1 0.8 0.2 0.3 0.7 file_2 0.1 0.9 0.2 0.8 file_3 0.5 0.5 0.7 0.3 ...

I wonder, whether there are ways/tricks to tell the model about the group information here: since group_a_co_1 + group_a_co_2 = 1 and the same goes for group_b. Somehow I figure if I expose the group information, the performance of my model will improve.

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The information in groups 'group_a_co_2' and 'group_b_co_2' are already redundant; they do not add more information to the model. Therefore they can be removed. Adding even more redundant information will not improve your model further.

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  • $\begingroup$ So you mean I just need group_a_co_1 and group_b_co_1 these two columns? $\endgroup$
    – dgg32
    Commented Dec 12, 2019 at 12:07
  • $\begingroup$ Yes, you will solve multicollinearity $\endgroup$
    – Syenix
    Commented Dec 13, 2019 at 20:03

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