Aug 15, 2017 · For WFSC and MFSC clusters, one feature is selected at a time for each cluster and the rest of the features are treated as redundant features.
Aug 15, 2017 · The proposed FCTFS strategy allows users to have deep understanding of the feature clusters with the help of their taxonomy. · The technique is ...
A flexible and user-guided feature subset selection algorithm, named as FCTFS (Feature Cluster Taxonomy based Feature Selection) has been proposed.
In this work, a flexible and user-guided feature subset selection algorithm, named as FCTFS (Feature Cluster Taxonomy based Feature Selection) has been proposed ...
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An extensive study has been conducted over 21 publicly available datasets, to evaluate viability of feature elimination strategy based on the values of the ...
This paper proposes a filter-based method for feature selection. The filter is based on the partitioning of the feature space into clusters of similar features.
Apr 3, 2019 · FeatureSelect is a feature or gene selection software application which is based on wrapper methods. Furthermore, it includes some popular filter methods.
[PDF] Clustering-based Sequential Feature Selection Approach for High ...
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At the first stage, features are divided into clusters by using a cluster- ing method based on graph-theoretic. Then, for each group, the feature the most ...
Missing: taxonomy | Show results with:taxonomy
Clustering based feature selection using Extreme Learning Machines ...
ieeexplore.ieee.org › document
Traditional k-means clustering technique along with TF-IDF and Wordnet helps us to form a quality and reduced feature vector to train the Extreme Learning ...
Missing: taxonomy | Show results with:taxonomy
Feature selection is the process of identifying a subset of the most useful features that produces compatible results as the original entire set of features.