As someone learning machine learning on my own, I’m reading the papers and running the code, but I’m not sure what’s wrong with increasing the number of eigenvectors and not seeing a significant change in recognition rate. I’m using a yaledatabase with a total of 15 sets, and I’m getting the recognition rate from leave one out for each set and then dividing by the total dataset, but I’m not sure what’s wrong…