Web Reference: In this paper, we will discuss what is meant by variable selection, why variable selection is important, the different methods for variable selection and their advantages and disadvantages. Using the study and the data, we introduce four methods for variable selection: (1) all possible subsets (best subsets) analysis, (2) backward elimination, (3) forward selection, and (4) Stepwise selection/regression. Variable selection means choosing among many variables which to include in a particular model, that is, to select appropriate variables from a complete list of variables by removing those that are irrelevant or redundant.
YouTube Excerpt: Quality and Technology group (www.models.life.ku.dk) LESSONS in CHEMOMETRICS:
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