Text mining with machine learning principles and techniques / Jan ¿ưi¿�ka, Machine Learning Consultant, Brono, Czech Republic, Franti¿Łek Da¿™ena, Department of Informatics, Mendel University, Brno, Czech Republic, Arno¿Łt Svoboda, Department of Applied Mathematics & Computer Science, Masaryk University, Brno, Czech Republic.

Author/creator ¿ưi¿�ka, Jan
Other author Da¿™ena, Franti¿Łek, 1979-
Other author Svoboda, Arno¿Łt, 1949-
Format Electronic
EditionFirst.
Publication InfoBoca Raton : CRC Press, 2019.
Descriptionxii, 351 pages : illustrations (some color) ; 25 cm
Supplemental ContentFull text available from Taylor & Francis eBooks
Subjects

Contents 1. Introduction to Text Mining with Machine Learning -- 2. Introduction to R -- 3. Structured Text Representations -- 4. Classification -- 5. Bayes Classifier -- 6. Nearest Neighbors -- 7. Decision Trees -- 8. Random Forest -- 9. Adaboost -- 10. Support Vector Machines -- 11. Deep Learning -- 12. Clustering -- 13. Word Embeddings -- 14. Feature Selection -- References -- Index -- Color Section.
Abstract "This book provides a perspective on the application of machine learning-based methods in knowledge discovery from natural languages texts. By analysing various data sets, conclusions, which are not normally evident, emerge and can be used for various purposes and applications. The book provides explanations of principles of time-proven machine learning algorithms applied in text mining together with step-by-step demonstrations of how to reveal the semantic contents in real-world datasets using the popular R-language with its implemented machine learning algorithms. The book is not only aimed at IT specialists, but is meant for a wider audience that needs to process big sets of text documents and has basic knowledge of the subject, e.g. e-mail service providers, online shoppers, librarians, etc"-- Provided by publisher.
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
LCCN 2019035868
ISBN9781138601826 (hardback)

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