Randomization methods for assessing data analysis results on real‐valued matrices

DOI10.1002/sam.10042OpenAlexW3083682711MaRDI QIDQ4969690

Markus Ojala, Aleksi Kallio, Niina Haiminen, Heikki Mannila, Niko Vuokko

Publication date: 14 October 2020

Published in: Statistical Analysis and Data Mining: The ASA Data Science Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/sam.10042

zbMATH Keywords

Markov chain Monte Carlodata miningDNA microarrayrandomization testssignificance testingreal-valued matrix

Mathematics Subject Classification ID

Statistics (62-XX) Computer science (68-XX)

Related Items (2)

Bsig: evaluating the statistical significance of biclustering solutions ⋮ The blind men and the elephant: on meeting the problem of multiple truths in data from clustering and pattern mining perspectives

Uses Software

• k-means++

Cites Work

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