Data mining - Info and Reading Options
practical machine learning tools and techniques with Java implementations
By I. H. Witten, Ian H. Witten and Eibe Frank
"Data mining" was published by Morgan Kaufmann in 2000 - San Francisco, Calif, it has 371 pages and the language of the book is English.
“Data mining” Metadata:
- Title: Data mining
- Authors: I. H. WittenIan H. WittenEibe Frank
- Language: English
- Number of Pages: 371
- Publisher: Morgan Kaufmann
- Publish Date: 2000
- Publish Location: San Francisco, Calif
- Library of Congress Classification: QA76.9.D343 W58 2000QA76.9.D343W58 2000
“Data mining” Subjects and Themes:
- Subjects: ➤ Data mining - Java (Computer program language) - Artificial intelligence - Data capture & analysis - Databases & data structures - Disaster Recovery - Data Modeling & Design - Database Engineering - Machine Learning - Computers - Computers - Data Base Management - Database Management - General - Computer Books: Internet General - Database Management - Database Mining - Artificial Intelligence - General - Programming Languages - Java - Computers / Information Storage & Retrieval - Computer Bks - Data Base Management - Java (Computer program languag - General - Intelligence (ai) & semantics - Professional, career & trade -> computer science -> database management - 762 - 077 - Professional, career & trade -> computer science -> intelligence (ai) & semantics - Java (Langage de programmation)
Edition Specifications:
- Pagination: xxvi, 371 p. ;
Edition Identifiers:
- The Open Library ID: OL15497072M - OL3961218W
- Online Computer Library Center (OCLC) ID: 42420775
- Library of Congress Control Number (LCCN): 99046067
- ISBN-10: 1558605525
- All ISBNs: 1558605525
AI-generated Review of “Data mining”:
"Data mining" Description:
The Open Library:
"This book offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining - including both tried-and-true techniques of the past and Java-based methods at the leading edge of contemporary research. If you're involved at any level in the work of extracting usable knowledge from large collections of data, this clearly written and effectively illustrated book will prove an invaluable resource."--Jacket.
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