I'm new to machine learning domain. I want to build a Classification tree for Binary classification of data.
I have a training data set of 269 records out of which 56 records belong to 'yes' class and 213 records to 'no' class.
Is this data imbalanced for building CART model? Do I need to undersample 'no' class records? Also from Gini index, Chi-Square and Information Gain, which algorithm is best for node splitting?
P.S.:- I can't increase the size of the dataset further.