Introduction to Data Mining

Pre-preparation and pre-processing are the most time-consuming process in KDD.

Data normalization is useful, but not necessary in general.

Handling missing data is a straightforward procedure.

Feature Discretization can be performed without class information.

Feature Selection is basically a search problem for finding an optimal subset of features.

Sampling is not a costly procedure. That is the reason for using sampling when dealing with large datasets.