Machine learning Data modelling

Feature Engineering:

1.     Adding or dropping feature

a.     Choose the feature that has most signals

2.     Combine multiple feature into one feature

a.     Represent the data in the simplest way possible(like all measurements in feet rather than some in inches

3.     Binning

a.     Replace an exact numerical measurement with a broader category. Like replacing unwanted extra measurement into True or False (like size of pool which is not that important rather having or not having pool is important)

4.     One-hot encoding

a.     A way to represent categorical data as number without creating

Also it’s advisable to have atleast 10x rows for X number of features