I am using a very large ~700,000 sample training set and ~700,000 sample testing set and training an SVM with the training set. When I run the SVM (SciKit-Learn) on the testing set it outputs only 0's. I was wondering why this would be? Do I need to reduce the dimensionality by running PCA or some other feature reduction algorithm?
The data consists of 293 features made up of a mixture of binary and continuous features.