Standarization before feature selection

Hi Everyone, I have a general question: Is it necessary to standarize (e.g. zscore) the data before feature selection? And if yes - why?

Thank you in advance, Best regards Michael

[mohan gopal]

ya feature extraction gives details ragarding the object area and background area as well it gives infm regarding the characteristics of the object , i hope its more beneficial to formulate a data base for feature selection in case of image processing

Answer 1

[Arturo Moncada-Torres]

It all depends on your application. It is not a golden rule, but can be handy in some cases.

For example, let's suppose you will use these features for a machine learning application. If you are going to feed them to a C4.5 classification algorithm, I think it will not make a big difference because of the nature of the algorithm per se. However, if you are going to feed them to a Nearest-Neighbor classifier, it would be a good idea, since normalizing the data will allow the coordinated system to be more "congruent" (I can not find a better word).

So in a concrete sentence, it is not necessary, but it can be useful sometimes.