Data Mining Algorithms In R
Publisher: Wikibooks 2010
In general terms, Data Mining comprises techniques and algorithms, for determining interesting patterns from large datasets. There are currently hundreds (or even more) algorithms that perform tasks such as frequent pattern mining, clustering, and classification, among others.
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by Anand Rajaraman, Jeffrey D. Ullman - Stanford University
At the highest level of description, this book is about data mining. However, it focuses on data mining of very large amounts of data. Because of the emphasis on size, many of our examples are about the Web or data derived from the Web.
by Jimmy Lin, Chris Dyer - Morgan & Claypool Publishers
This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns.
by Chuck Ballard, et al. - IBM Redbooks
It covers data modeling techniques for data warehousing, within the context of the overall data warehouse development process. The process of data warehouse modeling, including the steps required before and after the actual modeling, is discussed.
by J. M. Hellerstein, M. Stonebraker - UC Berkeley
These lecture notes provide students and professionals with a grounding in database research and a technical context for understanding recent innovations in the field. The readings included treat the most important issues in the database area.