For the titanic dataset, I have done some feature engineering (one-hot encoded the features) and now I have developed a heatmap to view the correlation between different features.
I'm not able to understand what to do with them. Lets say two features are highly correlated, eg, in the image,
sex_0(ie. male) are having correlation factor of 0.84. So, does that mean I should drop
sex_0is a very important feature. (This we know with experience, that sex in titanic is very important but is there any way we could view this as well by just observing the heatmap?).
One more doubt I have is: How would I know that I can just add two features, like
parch? I have seen many kernels where they just create one feature with
no_of_family_membersby just adding
sibsp=1) seems to be highly negatively correlated. Should I consider some action on this as well?