Feature extraction
This type of data transformation is very similar to attribute construction. In both, we use our deep knowledge of the original data to drive transformed attributes that are more helpful for our analysis purposes.
In attribute construction, we either come up with a completely new attribute from scratch or combine some attributes to make a transformed attribute that is more useful; however, in feature extraction, we unpack and pick apart a single attribute and only keep what is useful for our analysis.
As always, we will go for the best way to learn what we just discussed – examples! We will see some illuminative examples in this arena.
Example – extract three attributes from one attribute
The following figure shows the transformation of the Email attribute into three binary attributes. Every email ends with @aWebAddress; by looking at the website address providing the email service, we have extracted the three Popular Free Platform, .edu...
