HIGHLIGHTS
- who: Grzegorz Mrukwa from the Department of Data Science University of Technology, Poland have published the research work: DiviK: divisive intelligent K-means for hands-free unsupervised clustering in big biological data, in the Journal: (JOURNAL)
- what: The authors propose DiviK: a scalable stepwise algorithm with local data-driven feature space adaptation for segmenting high-dimensional datasets. The authors propose a hybrid framework that directly answers the above drawbacks: Divisive intelligent K-means (DiviK). The authors propose to use a feature filtering procedure based on GMM decomposition . As the authors aim for a hands-free . . .
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