In machine learning the random subspace method, also called attribute bagging or feature bagging, is an ensemble learning method that attempts to reduce the correlation between estimators in an ensemble by training them on random samples of features instead of the entire feature set. == Motivation == In ensemble learning one tries to combine the models produced by several learners into an ensemble that performs better than the original learners.
In machine learning the random subspace method, also called attribute bagging or feature bagging, is an ensemble learning method that attempts to reduce the correlation between estimators in an ensemble by training them on random samples of features instead of the entire feature set. == Motivation == In ensemble learning one tries to combine the models produced by several learners into an ensemble that performs better than the original learners.
Source: Wikipedia "Random subspace method" · CC BY-SA 4.0
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