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Data Mining

Data Mining Using SAS Enterprise Miner

The most thorough and up-to-date introduction to data mining techniques using SAS Enterprise Miner.

The Sample, Explore, Modify, Model, and Assess (SEMMA) methodology of SAS Enterprise Miner is an extremely valuable analytical tool for making critical business and marketing decisions. Until now, there has been no single, authoritative book that explores every node relationship and pattern that is
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Java Data Mining: Strategy, Standard, and Practice: A Practical Guide for architecture, design, and implementation

This is not only a great introduction to JDM, but also a great introduction for a practitioner to data mining in general. This is a must have” for anyone developing large scale data mining applications in Java.
Robert Grossman, Open Data Group and University of Illinois at Chicago
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Mining Graph Data

Discover the latest data mining techniques for analyzing graph data

This text takes a focused and comprehensive look at an area of data mining that is quickly rising to the forefront of the field: mining data that is represented as a graph. Each chapter is written by a leading researcher in the field; collectively, the chapters represent the latest findings and applications in both theory and practice, including solutions to many of the algorithmic challenges that arise in mining graph data.
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Business Modeling and Data Mining

Business Modeling and Data Mining demonstrates how real world business problems can be formulated so that data mining can answer them. The concepts and techniques presented in this book are the essential building blocks in understanding what models are and how they can be used practically to reveal hidden assumptions and needs, determine problems, discover data, determine costs, and explore the whole domain of the problem.
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Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining

A practical, step-by-step approach to making sense out of data

Making Sense of Data educates readers on the steps and issues that need to be considered in order to successfully complete a data analysis or data mining project. The author provides clear explanations that guide the reader to make timely and accurate decisions from data in almost every field of study. A step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. With a comprehensive collection of methods from both data analysis and data mining disciplines, this book successfully describes the issues that need to be considered, the steps that need to be taken, and appropriately treats technical topics to accomplish effective decision making from data.
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