I have a code written in python that include Naive Bayes, Random Forest and Decision Tree in order to predict Churn of customers in telecom industry. The accuracy is around 70%. I need to get more accuracy for those models. I need someone who could try different methods to increase that accuracy. This could be done by using better feature selection or cross-validation. Any other methods that comes to your mind, would be highly appreciated. I attached the code that needs to be improved and dataset.
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