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Visualized Classification of Multiple Sample Types - Computer - cs rpi

Visualized Classification of Multiple Sample Types - Computer - cs rpi 2025

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The document presents a novel interactive visualization approach called VizCluster for classifying multiple types of gene expression samples using DNA microarray technology. It discusses the process of identifying informative genes, building classifiers based on visual data distribution, and evaluating their performance through various datasets. The study demonstrates the effectiveness of VizCluster in revealing underlying data patterns and achieving satisfactory classification accuracy across different sample types, thus contributing to advancements in bioinformatics and data mining.

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