I am novice in DS/ML stuff. I am trying to solve Titanic case study in Kaggle, however my approach is not systematic till now. I have used correlation to find relationship between variables and have used KNN and Random Forest Classification, however my models performance has not improved. I have selected features based on the result of correlation between variables.
Please guide me if there are certain sk-learn methods which can be used to identify features which can contribute significantly in forecasting.
