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Second, for feature selectors, the stability of FS is mainly improved by combining different feature selection methods. The performance of each feature selector is different. In the integration process, each feature selector's different performance is not considered.
We propose an entropy based measure which can assess the stability of feature selection methods with respect to perturbations in the data. Results show that ...
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Feature selection technique is a knowledge discovery tool which provides an understanding of the problem through the analysis of the most relevant features.
We recommend augmenting statistical feature selection methods with concurrent analysis on stability and reproducibility to improve the quality of the selected ...
There are several possible ways to improve stability of feature selection algorithms such as using prior information and knowledge, feature grouping, and ...
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Abstract. An improper design of feature selection methods can often lead to incorrect conclusions. Moreover, it is not generally realised that.
We propose an entropy based measure which can assess the stability of feature selection methods with respect to perturbations in the data. Results show that ...
Sep 12, 2023 · The method we present in this letter improves the stability of the delta test, thereby increasing the trustworthiness of the feature selection ...
We propose an entropy based measure which can assess the stability of feature selection methods with respect to perturbations in the data. Results show that ...
Apr 28, 2022 · The stability of feature selection generally refers to the robustness of the obtained feature subsets against variations in the training data.