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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:
When you create a resume and cover letter, specific word choices help your resume stand out from the competition. Tailoring your content to fit the job description and including key words reflects your ability to identify job demands associated with the position. Some employers use scanning programs to locate the best resumes and reject those that don't meet minimal standards.