Some researchers have developed algorithms just for the selection of relevant features [3, 13-15]. In this paper we present a classification learning algorithm�...
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Jun 27, 2006 � In this paper, we describe a recently proposed classification algorithm called VFI5, which achieves comparable accuracy to nearest-neighbor�...
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Feb 10, 2024 � Strategies for handling irrelevant features in ML include feature selection methods like filter, wrapper, or embedded approaches. Dimensionality�...
Oct 27, 2018 � The answer is yes, highly similar instances in your dataset that have different target classes will cause your model to perform poorly.
In particular, the FIL.IF algorithm is robust to the presence of irrelevant features. Real classification problems often involve missing feature values.