Data Mining: Concepts and Techniques, Second Edition. Jiawei Han and Micheline Kamber. Querying XML: XQuery, XPath, and SQL/XML in context. Jiawei Han and Micheline Kamber. Data Mining: Concepts and Techniques,. The Morgan Kaufmann Series in Data Management Systems, Jim Gray, Series Editor Morgan Kaufmann Data Warehouse and OLAP Technology for Data Mining. Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems) [Jiawei Han, Micheline Kamber, Jian Pei] on.

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An Environment of Computational Intelligence. SQL in a Nutshell. Mastering Predictive Analytics with Python.

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Home eBooks Nonfiction Data Mining: Would you like us to take another look at this review? No, cancel Yes, report it Thanks! Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Big Data Analytics and Knowledge Discovery. 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.

Analytic Methods in Systems and Software Testing. Databases Theory and Applications. A General Introduction to Data Analytics. It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets.


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Data Mining: Concepts and Techniques – Jiawei Han – Google Books

The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. Or, get it for Kobo Super Points! Advances in K-means Clustering. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described.

Written expressly for database practitioners and professionals, this book begins with a conceptual introduction designed to get you up to speed.

Wherever possible, the authors raise and answer questions of utility, feasibility, optimization, and scalability, keeping your eye datx the issues that will affect your project’s results and your overall success. Database Systems for Advanced Applications.

It then presents information about data warehouses, online analytical processing OLAPand data cube technology. See if you have enough points for this item. This book is intended for Computer Science students, qnd developers, business professionals, and researchers who seek information on data mining. Mining Heterogeneous Information Networks.

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Concepts and Techniques Back to Nonfiction. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, ebooo data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data.

Pro Power BI Desktop. Formal Aspects of Component Software. Machine Learning for Text. Classroom Features Available Online: Concepts and Techniques equips you with a sound understanding of data mining principles and teaches you proven methods for knowledge discovery in large corporate Data Mining Applications with R.

Specifically, it explains data mining and the tools used in discovering knowledge from the collected data.