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Machine learning and. In machine learning and statistics, feature selection, also known as variable selection, attribute selection or variable subset selection, is the process of selecting a subset of relevant features (variables, predictors) for use in model construction. Feature selection techniques are used for three reasons:
A summary may not be the best lead for a feature. A lead block of one or two paragraphs often begins a feature. Rather than put the news elements of the story in the lead, the feature writer uses the first two or three paragraphs to set a mood, to arouse readers, to invite them inside. Then the news peg or the significance of the story is provided in the third or fourth paragraph, the nut graph.