Feature selection

PCA for dimensionality reduction

for 10 features in our dataset, after we apply PCA, it gives us 10 Reformulated features, in which most cases, First 2 to 3 feaures would have covered the essence of all features.

we still have those remaning 7 features of PCA, which might not retain much informations.