Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)

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Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems) ISBN  0120884070 Release Date  10 June 2005 Category  Data Mining Tags  mining,   "data mining",   data mining,   "machine learning",   machine learning,   machine,   0120884070,   learning,   forensics technique,   data mining: practical machine learning tools and techniques,   data mining: concepts and techniques,   data mining concepts and techniques,   text mining,   data mining: practical machine learning tools and techniques (second edition),   knowledge management,   project management,   "data mining: practical machine learning tools and techniques",   kaufmann,   morgan kaufmann,   practical machine learning tools and techniques,   frank,   virtual machine,   "practical machine learning",   pattern recognition and machine learning,   operating system,   This book @Amazon  View Tools Google Search Web flazx.com

Description This is the second edition of the author's Data Mining book. The first part of the book focuses on data mining algorithms, implementation issues, and how to evaluate the results of the data mining model. The second part focuses on the authors "Weka Machine Learning Workbench" which is available under a GNU General Public License. See their web site: http://www.cs.waikato.ac.nz/~ml/weka/index.html for the software. This software appears to be widely used at academic institutions. The first section of the book provides an overview of the algorithms that the software implements. If you need an in depth understanding of the algorithms, you will need additional information sources. If you simply download the software without an understanding of which algorithms are appropriate to your data mining problem, you may become frustrated with the performance, or, even worse, you may misinterpret the results of the data mining model. In general, learning data mining is much more complex than this book (or any other single book) can adequately describe; however, this is an excellent source for someone interested in data mining. Other books on Data Mining Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing) Visual Data Mining: Theory, Techniques and Tools for Visual Analytics (Lecture Notes in Computer Science) Privacy-Preserving Data Mining: Models and Algorithms (Advances in Database Systems) Fuzzy Modeling Tools for Data Mining and Knowledge Discovery (The Morgan Kaufmann Series in Data Management Systems) Advanced Data Mining Techniques Data Mining and Knowledge Discovery Technologies (Advances in Data Warehousing and Mining) Mobility, Data Mining and Privacy: Geographic Knowledge Discovery Survey of Text Mining II: Clustering, Classification, and Retrieval Emerging Technologies of Text Mining: Techniques and Applications Data Mining Patterns: New Methods and Applications Data Mining With Ontologies: Implementations, Findings and Frameworks (Premier Reference) Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage Principles of Data Mining (Undergraduate Topics in Computer Science) Intelligent Data Mining: Techniques and Applications (Studies in Computational Intelligence) Research And Trends in Data Mining Technologies And Applications (Advances in Data Warehousing and Mining Series) (Advances in Data Warehousing and Mining ... in Data Warehousing and Mining Series)