How do I compare traditional classifiers performance with my proposed method? I want to compare my proposed method with traditional machine learning classifiers like Multilayer Perceptron(MLP) and SVM to check the classification accuracy.How do I compare different classifiers?. I want to draw a comparison between these three terms


1).Proposed method (Based on DNN) 
2).Shallow neural networks
3).SVM
What about doing cross validation on your training set? Once you have the different train/test splits I would start by printing the accuracy (number of correct predictions / total predictions) and the confussion matrix for each method.

If you are using python sklearn.metrics offers a wide variety of useful functions.