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In this paper, a new computational method is proposed to approximate the conditional mutual information between the selected features and the decision feature, ...
In this paper, a new computational method is proposed to approximate the conditional mutual information between the selected features and the decision feature, ...
In this paper, a new computational method is proposed to approximate the conditional mutual information between the selected features and the decision feature, ...
In this paper, a new computational method is proposed to approximate the conditional mutual information between the selected features and the decision feature, ...
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Aug 17, 2022 · We first propose a robust fuzzy rough set model based on data distribution to achieve the purpose of anti-noise ie, Noise-aware Fuzzy Rough Sets (NFRS) model.
In this paper, we propose a fuzzy rough unlearning framework, called Attribute Reduction Unlearning algorithm (ARU), which unlearns the outdated instances from ...
Gaussian kernel based fuzzy rough sets merges kernel method to fuzzy-rough sets for efficient feature selection. This works aims at improving the computational ...
Fuzzy rough sets is an extension to classical rough sets. The fuzzy rough set model is useful in feature selection for hybrid decision systems. Fuzzy decision ...
Jan 10, 2019 · In this paper, we design a feature selection strategy for hierarchical classification based on fuzzy rough sets. First, a fuzzy rough set model ...
An efficient technique is presented based on Fuzzy rough set theory to pre-process the large-scale data sets to increase the efficacy of the predictive ...