Cluster Sampling Method
Frequency-dependent Selection
Sampling Plans
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Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
Miodrag Zivkovic1, Catalin Stoean2, Amit Chhabra3
1Faculty of Informatics and Computing, Singidunum University, Danijelova 32, 11010 Belgrade, Serbia.
This study introduces a novel swarm intelligence algorithm for feature selection, effectively reducing data noise and identifying key attributes. The method significantly improves classification accuracy and reduces feature count in machine learning models.
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