I am wondering, if it is necessary to remove outliers from the dataset if we perform Normalisation on the data as after Normalisation, all the values will shrink to value between 0 and 1. So, is it necessary?
Normalisation is used to transform all variables in the data to a same range. It doesn't solve the problem caused by outliers.
Just to give an example,
Suppose, following are the data-points:
It is clear that 990 and 1000 are the outliers here.
Using Min-max Normalisation, these data-points will transform to the following:
0, 0.002, 0.005, 0.01, 0.015, 0.02, 0.022, 0.024, 0.99, 1
So, as you can see the after normalisation also, the outliers remains outliers. Only the range is changed.
Here, I have used Min-max Normalisation, but any normalisation technique will change the range only, and in all the cases outliers will remain outliers after normalisation.