Statistical machine learning is a branch of mathematics concerned with developing algorithms for data analysis. This thesis presents new mathematical models and statistical software, and is organized into two parts. In the first part, I present several new algorithms for clustering and segmentation. Clustering and segmentation are a class of techniques that attempt to find structures in data. I discuss the following contributions, with a focus on applications to cancer data from bioinformatics. In the second part, I focus on statistical software contributions which are practical for use in everyday data analysis.
Identifer | oai:union.ndltd.org:CCSD/oai:tel.archives-ouvertes.fr:tel-00906029 |
Date | 20 November 2012 |
Creators | Hocking, Toby Dylan |
Publisher | École normale supérieure de Cachan - ENS Cachan |
Source Sets | CCSD theses-EN-ligne, France |
Language | English |
Detected Language | English |
Type | PhD thesis |
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