I have two matrices deriving from one matrix of the original data. One is the training, the other is the validation set. Each matrix has rows= examples, columns = featuers. The proportions are 65% vs 35% respectively.
Given that the data is in many dimensions and it is not possible to visualize it, what would you suggest to use to make predictions ?
I was initially thinking about a polynomial fit, but how does one know which of the 65 features to square, cube, etc?