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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It can also be an excellent handbook for researchers in the area of data mining and data warehousing. Machine Learning and Security. How to write a great review Do Say what you liked best and least Describe the author’s style Explain the rating you gave Don’t Use rude and profane language Include any personal information Mention spoilers or the book’s price Recap the plot.

Overall rating No ratings yet 0. Applied Cryptography and Network Security. Python Machine Learning By Example. August 24, ISBN: Machine Learning for Developers. Redis Programming by Example. Mastering Text Mining with R. Ratings and Reviews 0 0 star ratings 0 reviews. Introduction to Information Retrieval. Data Mining Techniques addresses all the major and latest techniques of data mining and data warehousing.

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The book also discusses the mining of web data, spatial data, temporal data and text data. Continue shopping Checkout Continue shopping. It deals in detail with the latest algorithms for discovering association rules, decision trees, clustering, neural networks and genetic algorithms.

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The revised edition includes a comprehensive chapter on rough set theory. Data Mining Techniques by Arun K.

Data Mining – Arun K. Pujari

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. This book can serve as a textbook for students of computer science, mathematical science and management science.

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Data Mining – Arun K. Pujari – PDF Drive

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Data Mining and Constraint Programming. Data Analysis for Network Cyber-Security. The rough set theory, which is a tool of sets and relations for studying imprecision, vagueness, and uncertainty in data analysis, is a relatively new mathematical and artificial intelligence technique.

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