Why we need to convert Numeric Variable into Categorical variable in Model Building?

machine_learning

#1

We often do converting variables nature in Model building, Why we need to do that, what is the advantage we will get, can any one help me …


#2

@sekhar_chandra630-by creating the output as factor it helps the model to know the level or categories of output in which model has to classify.

Hope this helps!
Regards,
hinduja1234


#3

I think question is not clear framed, During model building we will go for pre-processing suppose i have a numeric variable having values range from 1 to 10,000 then i brought binning concept and i made 10 bins, By doing this what advantage i will get my model performance is increased apart from this do we have any specific reason why we converted it into factor.


#4

@sekhar_chandra630-when you make factor it will increase the efficiency of your model because handling of large variable is not easy it is better to reduce to handled size and if you will not reduce to factors your model will still works and might be possible that it will give same result.So it is better to work with less variable.

Hope this helps!
Regards,
hinduja1234