I have a bunch of features that I would like to use for classification/machine learning and cluster analysis. Normally I use single point values or transformations of values for features and everything is fine
Now I would like to use a matrix as a feature. The matrix is probably going to be a fairly big (say 50x50) but will only be filled with 1's and 0's. It is pretty much an 'image' matrix. It is the shape/pattern of the matrix entries which is important.
Is there anyway I can easily use the matrix as a feature for machine learning? I know I could use each matrix entry, say Row1Column1 as a feature and then give it a value, but then I would have 2500 features from my 50x50 matrix, which is what I am trying to get away from.
Any ideas would be greatly appreciated.