Provides a comprehensive textbook covering theory and practical examples for a course on data mining and data warehousing.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Parteek Bhatia is an associate professor in the department of computer science and engineering at Thapar Institute of Engineering and Technology, Patiala. He has more than twenty years of teaching experience and has published papers in journals. His current research includes natural language processing, machine learning and human computer interface. He has taught courses including data mining and data warehousing, big data analysis and database management system at undergraduate and graduate levels.
Inhaltsangabe
Preface Acknowledgement Dedication 1. Beginning with machine learning 2. Introduction to data mining 3. Beginning with Weka and R language 4. Data pre-processing 5. Classification 6. Implementing classification in Weka and R 7. Cluster analysis 8. Implementing clustering with Weka and R 9. Association mining 10. Implementing association mining with Weka and R 11. Web mining and search engine 12. Operational data store and data warehouse 13. Data warehouse schema 14. Online analytical processing 15. Big data and NoSQL Reference Index.
Preface Acknowledgement Dedication 1. Beginning with machine learning 2. Introduction to data mining 3. Beginning with Weka and R language 4. Data pre-processing 5. Classification 6. Implementing classification in Weka and R 7. Cluster analysis 8. Implementing clustering with Weka and R 9. Association mining 10. Implementing association mining with Weka and R 11. Web mining and search engine 12. Operational data store and data warehouse 13. Data warehouse schema 14. Online analytical processing 15. Big data and NoSQL Reference Index.
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