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An Introduction to Support Vector Machines -- First comprehensive introductory book to the field of Support Vector Machines, a novel machine learning algorithm.
Bibliography of SOM papers -- A collection of works that have been based on the Self-Organizing Map (SOM) method developed by Kohonen
Machine Learning on Non-Homogeneous, Distributed Text Data -- PhD thesis: Dunja Mladenic, University of Ljubljana, Slovenia. An approach to automatic document categorization based on a large categorization hierarchy is proposed.
Machine Learning, Neural and Statistical Classification -- This book is based on the EC (ESPRIT) project StatLog which compare and evaluated a range of classification techniques, with an assessment of their merits, disadvantages and range of application. This integrated volume provides a concise introduction to each method, and reviews comparative trials in large-scale commercial and industrial problems. It makes accessible to a wide range of workers the complex issue of classification as approached through machine learning, statistics and neural networks, encouraging a cross-fertilization between these discplines.
T.-S. Lim''s Bibliography on Tree-Structured Methods -- Extensive bibliography collection related to recursive partitioning based learning methods; e.g., classification and regression trees.
The Collection of Computer Science Bibliographies -- BibTeX entries of around 830,000 references from journal articles, conference papers and technical reports from 1,200 computer science-related bibliographies.
Warren S. Sarle''s Bibliography on Cluster Analysis -- Useful clustering literature collected by Warren S. Sarle and originally published in the SAS/STAT User''s Guide (1990)

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