I have a dataset of 4712 records and 60+ features working on a binary classification problem. I already tried out all the feature selection approaches like
filter, embedded and wrapper but am just curious to learn and try
genetic algorithm for feature selection.
The reason for choosing
genetic algorithm is because I guess it will just provide me the best model fit based on best features.
1) I understand it might take time but would you people help me know how can I do this in Python?
2) In addition, is
genetic algorithm any different or better than all other feature selection approaches discussed above? What are its disadvantages?
Is there any python packages and tutorial available on how to use this?
I see tutorials but they all about the theory of genetic algorithm
Can you help me by sharing any tutorial or package for genetic algorithm?