Text mining with machine learning : principles and techniques /
Žižka, Jan,
Text mining with machine learning : principles and techniques / Jan Žižka, František Dařena, Arnošt Svoboda. - 1 online resource
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.
"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"--
9780429469275 0429469276 9780429890260 0429890265 9780429890253 0429890257 9780429890277 0429890273
Machine learning.
Computational linguistics.
Semantics--Data processing.
COMPUTERS / Database Management / Data Mining
COMPUTERS / Machine Theory
MATHEMATICS / Arithmetic
Q325.5 / .Z59 2020
006.3/12
Text mining with machine learning : principles and techniques / Jan Žižka, František Dařena, Arnošt Svoboda. - 1 online resource
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.
"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"--
9780429469275 0429469276 9780429890260 0429890265 9780429890253 0429890257 9780429890277 0429890273
Machine learning.
Computational linguistics.
Semantics--Data processing.
COMPUTERS / Database Management / Data Mining
COMPUTERS / Machine Theory
MATHEMATICS / Arithmetic
Q325.5 / .Z59 2020
006.3/12
