Feature selection also helps people to acquire better understanding about their data by telling them which are the important features and how they are related with each other.
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Feature selection Not extracting new features but rather removing features which seem irrelevant for modeling. This is a combinatorial optimization problem.
Feature Selection
One of the preliminary stage in predictive data mining, ...
This is called feature selection or feature extraction. Feature selection and SVM classification together have a use even when prediction of unknown samples is not necessary.
The first purpose is feature selection and the second purpose is classification.
"My own research in intrusion detection concerned using feature selection to build better classifiers explicitly for use as intrusion detection systems.
RandomForests perform poorly over a variety of parameters. I didn't experiment much with feature selection (such as by PCA - takes too long) and I'm not sure which features others are using. Send me your datasets and I'll run them.
 See also: Classification, Neural network, Distribution, Data mining, Regression
  
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