[PDF.64zx] Applied Biclustering Methods for Big and High-Dimensional Data Using R (Chapman & Hall/CRC Biostatistics Series)
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Applied Biclustering Methods for Big and High-Dimensional Data Using R (Chapman & Hall/CRC Biostatistics Series)
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| #4486691 in Books | 2016-10-04 | Original language:English | PDF # 1 | 9.25 x6.25 x1.00l,.0 | File type: PDF | 433 pages||About the Author||Adetayo Kasim is a senior research statistician at Durham University. | |Ziv Shkedy is a professor in the Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat) in the Center for Statistic
Proven Methods for Big Data Analysis
As big data has become standard in many application areas, challenges have arisen related to methodology and software development, including how to discover meaningful patterns in the vast amounts of data. Addressing these problems, Applied Biclustering Methods for Big and High-Dimensional Data Using R shows how to apply biclustering methods to find local patterns in a big data matrix.
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