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Home Blog Week #5 – Features vs. Variables

Week #5 – Features vs. Variables

The predictors in a predictive model are sometimes given different terms by different disciplines.  Traditional statisticians think in terms of variables.

The machine learning community calls them features (also attributes or inputs).  There is a subtle difference in meaning.  In predictive modeling, depending on the nature of the data, considerable work may be required to transform and winnow down data and text to a usable set of predictors.  This process is termed “feature engineering.”  The comparable term in statistics – “variable selection” – does not imply such a wide ranging process.

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