High Dimensional Data
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Revolutionizing Cancer Diagnosis: Unleashing the Tab Transformer's Power for Accurate Classification
Abstract: Gene expression platforms offer vast amounts of data that can be utilized for investigating diverse biological processes. However, the presence of redundant and irrelevant genes makes it challenging to identify crucial genes from high-dimensional biological data. To overcome this obstacle, researchers have introduced different feature selection (FS) methods. Developing more efficient and accurate feature selection techniques is essential for selecting important genes in complex biological information with multiple dimensions. In …
Published in Research and Reviews : Journal of Computational Biology · Vol. 12, Issue 2, 2023 · pp. 24–38 Read article