I am trying to increase my accuracy from 96% in the Digit Recogniser problem in Kaggle.I have currently used only Random Forest and trying with KNN and SVM.
I guess I will have to use ensemble methods for this one and hence I would like to know a few things:
1.Do i divide the training data into multiple sets and use the same algorithm on them and then combine the results? OR
2.Do I use multiple algorithms on the train data and then combine their predictions??
In this type of a classification problem if I divide the dataset into multiple datasets,some digits might be left out in a particular dataset-will this not reduce the power of the particular algo I am applying??
These are some of the considerations I would like to know before proceeding with ensembles,so can somebody please help me with these.