I have a very large training set where each of the feature's datapoints are very similar (float values in the range
For example, following is some part of the training data :
where the last column is the class-label - only 0 and 1.
How should I handle this kind of data if the training set is very very large (> 100k) ?
Please suggest an appropriate classifier (using
scikit-learn) as well.