Dimension reduction and classifier-based feature selection for oversampled gene expression data and cancer classification
Gene expression data are usually known for having a large number of features. Usually, some of these features are irrelevant and redundant. However, in some cases, all features, despite being numerous, show high importance and contribute to the data analysis. In a similar fashion, gene expression da...
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Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI
2023
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Subjects: | |
Online Access: | http://eprints.utm.my/106539/1/NaomieSalim2023_DimensionReductionandClassifierBasedFeature.pdf http://eprints.utm.my/106539/ http://dx.doi.org/10.3390/pr11071940 |
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Institution: | Universiti Teknologi Malaysia |
Language: | English |