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* Preprocessing for non-tree based methods->feature scaling, rank transformation, outliers management
* Feature generation: fractional parts, dividing 2 features to create a 3rd feature, combining 2 features to create a new feature
Categorical features:-
* Ordinal features and categorical features.
* Ordinal features have some meaningful order in them. e.g, designation of a person, class of some travelling i.e 1st class,2nd class,3rd class etc
* Categorical features, e.g sex of some person etc
* Label encoding, one-hot encoding, frequency encoding are used to convert categorical features to numeric features.
Datetime and coordinate features:-
Datetime-Periodicity, time-since, time difference etc
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