Assume I have an example set with m samples and n features. I have weighted these n features with a statistical weighting method (like Gini, Chi-squared, InfoGain, etc.). Now I have n normalized weighted features. How can I probabilistically choose p features from these n features? (p << n) // p is very smaller than n I want each feature have a probability to be chosen amongst these p features and this probability should be its normalized weight.
Can anybody help me? Please help me find the operator tree to solve this problem.