• alpha: regularization parameter
  • like regularized regression and SVM, require properly normalize the input features.
  • a good choice, when the features are of similar types. For example, all derived from the pixels of an image. And less of a good choice, when the features are of very different types.
  • one of the advantages of deep learning is that it includes a sophisticated automatic featured learning phase