Performance Analysis of Microarray Data Classification using Machine Learning Techniques

2. Feature Selection

In machine learning and statistics, feature selection, also known as variable selection, attribute selection or variable subset selection, is the method of selecting a subset of relevant features (variables, predictors) for use in model construction. Feature selection methods are used for three reasons:

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  Simplification of models to formulate them easier to interpret by researchers/users;

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  Shorter training times;

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  Enhanced generalization by decreasing overfitting (formally, reduction of variance).