Data Mining: Techniques. Front Cover. Arun K. Pujari. Universities Press, – pages Bibliographic information. QR code for Data Mining. Data Mining Techniques [Arun K Pujari] on *FREE* shipping on qualifying offers. Data Mining Techniques addresses all the major and latest. Data Mining Techniques – Arun K. Pujari – Ebook download as PDF File .pdf), Text File .txt) or read book online. Arun K Pujari.

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The Functional Approach to Programming. The book also discusses the mining of web data, spatial data, temporal data and text data. This book can serve as a textbook for students of computer science, mathematical science and management science. Professor Yanhong Annie Liu. Readings in Artificial Intelligence and Software Engineering. Close Report a review At Kobo, we try to ensure that published reviews do not contain rude or profane language, spoilers, or any of our reviewer’s personal information.

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Data Analysis with Open Source Tools. Interesting and recent developments such as Support Vector Machines and Rough Set Theory are also covered in the book.

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Artificial Intelligence for Big Data. The Theory of Info-Dynamics: The title should be at least 4 characters long. Advances in Databases and Information Systems. You can remove the unavailable item s now or we’ll automatically remove it at Checkout. The revised edition includes a comprehensive chapter on rough set theory.

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Mastering Text Mining with R. It can also be an excellent handbook for researchers in the area of data mining and data warehousing.

Continue shopping Checkout Continue shopping. Machine Learning for Evolution Strategies. The discussion on association rule mining has been extended to include rapid association rule mining RARMFP-Tree Growth Algorithm for discovering association rule and the Eclat and dEclat algorithms.

Integration of Reusable Systems. Machine Learning for Data Streams. Principles of Data Integration. Handbook of Constraint Programming. Schema Matching and Mapping. No, cancel Yes, report it Thanks! Advanced Machine Learning with Python. Big Data Analytics with R and Hadoop. Scalable Pattern Recognition Algorithms.