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terimler
mRMR (Minimum Redundancy Maximum Relevance)
Selection criterion optimizing the trade-off between maximum relevance of features with the target and their minimum mutual redundancy.
terimler
Univariate Feature Selection
Approach evaluating each feature independently against the target variable without considering interactions between variables.
terimler
Multivariate Feature Selection
Technique considering simultaneously the relationships and interactions between multiple features to optimize the global selection.
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