Feature (machine learning)

<p>In <a href="/facts/Machine_learning/e0w0XJTu">machine learning</a> and <a href="/facts/Pattern_recognition/o1s38opj">pattern recognition</a>, a feature is an individual measurable property or characteristic of a data set. Choosing informative, discriminating, and independent features is crucial to produce effective <a href="/facts/Algorithm/fnl5NmRt">algorithms</a> for <a href="/facts/Pattern_recognition/o1s38opj">pattern recognition</a>, <a href="/facts/Classification_(machine_learning)/jXXHRkXR">classification</a>, and <a href="/facts/Regression_analysis/n6z5Tf7K">regression</a> tasks. Features are usually numeric, but other types such as <a href="/facts/String_(computer_science)/4ChJu5WS">strings</a> and <a href="/facts/Graph_(discrete_mathematics)/kw3eIBUe">graphs</a> are used in <a href="/facts/Syntactic_pattern_recognition/NNRKuxrp">syntactic pattern recognition</a>, after some pre-processing step such as <a href="/facts/One-hot/d6YJwj3d">one-hot encoding</a>. The concept of "features" is related to that of <a href="/facts/Dependent_and_independent_variables/dINfzIF2">explanatory variables</a> used in statistical techniques such as <a href="/facts/Linear_regression/5n998IhK">linear regression</a>.
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Feature (machine learning) open-in-new

Feature (machine learning)