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Description
Learning algorithms and statistical software, with applications to bioinformaticsToby Dylan Hocking's PhD thesis is divided into two parts: learning algorithms and statistical software. Algorithms for segmentation, clustering, and model selection are discussed in the first part, and the second part explains how to implement several statistical software packages in the R language. The content, which includes 47 color figures, should be appreciated by a reader with a background in statistics, data analysis, machine learning, or
Toby Dylan Hocking's PhD thesis is divided into two parts: learning algorithms and statistical software. Algorithms for segmentation, clustering, and model selection are discussed in the first part, and the second part explains how to implement several statistical software packages in the R language. The content, which includes 47 color figures, should be appreciated by a reader with a background in statistics, data analysis, machine learning, or programming.
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