Support Vector Machine – Recursive Feature Elimination for Feature Selection on Multi-omics Lung Cancer Data
Nuraina Syaza Azman,
Azurah A Samah,
Ji Tong Lin
et al.
Abstract:Biological data obtained from sequencing technologies is growing exponentially. Multi-omics data is one of the biological data that exhibits high dimensionality, or more commonly known as the curse of dimensionality. The curse of dimensionality occurs when the dataset contains many features or attributes but with significantly fewer samples or observations. The study focuses on mitigating the curse of dimensionality by implementing Support Vector Machine – Recursive Feature Elimination (SVM-RFE) as the selecte… Show more
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