It presents the importance of feature selection in terms of reducing the number of features, enhancing the quality of machine learning and providing better ...
Abstract— Gene expression data is a very complex data set characterised by abundant numbers of features but with a low number of observations.
Aug 20, 2018 · Feature selection is currently a good choice for dimensionality reduction for microarray data. Accordingly, a powerful feature selection method ...
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This systematic review provides researchers interested in feature selection (FS) for processing microarray data with comprehensive information about the main ...
It presents the importance of feature selection in terms of reducing the number of features, enhancing the quality of machine learning and providing better ...
Feb 9, 2024 · In this paper, we address the problem of classifying cancer based on gene expression for handling the class imbalance problem and the curse of dimensionality.
In this paper, we carry out a systematic study to investigate the impact of gene selection on imbalanced microarray data. Our objective is to understand that if ...
Jun 15, 2005 · We apply an evolutionary algorithm to identify the near-optimal set of predictive genes that classify the data. We also examine the initial gene selection step.
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Apr 25, 2023 · Feature selection in high dimensional gene expression datasets not only reduces the dimension of the data, but also the execution time and ...
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This study proposes a new feature selection method that integrates Preordonnances theory in terms of new Relevance and Complementarity criteria introduced here.
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