Feature Selection and Extraction

The success of pattern recognition techniques can frequently be enhanced or simplified by suitable prior treatment of the analytical data, and feature selection and feature extraction are important stages in chemometrics. Feature selection refers to identifying and selecting those features present in the analytical data which are believed to be important to the success of calibration or pattern recognition. Techniques commonly used include differentiation, integration, and peak identification. Feature extraction, on the other hand, changes 

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In this chapter we have been able to discuss only some of the more common and basic methods of feature selection and extraction. This area is a major subject of active research in chemometrics. The effectiveness of subsequent data processing and interpretation is largely governed by how well our analytical data have been summarized by these methods. The interested reader is encouraged to study the many specialist texts and journals available to appreciate the wide breadth of study associated with this subject. 

Feature Selection and Extraction For correlation about the origin,... 

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