Data mining : a tutorial-based primer
著者
書誌事項
Data mining : a tutorial-based primer
（Chapman & Hall/CRC data mining and knowledge discovery series）（A Chapman & Hall book）
CRC Press, c2017
2nd ed
- : [pbk.]
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注記
Includes bibliographical references (p. 461-464) and index
内容説明・目次
内容説明
Data Mining: A Tutorial-Based Primer, Second Edition provides a comprehensive introduction to data mining with a focus on model building and testing, as well as on interpreting and validating results. The text guides students to understand how data mining can be employed to solve real problems and recognize whether a data mining solution is a feasible alternative for a specific problem. Fundamental data mining strategies, techniques, and evaluation methods are presented and implemented with the help of two well-known software tools.
Several new topics have been added to the second edition including an introduction to Big Data and data analytics, ROC curves, Pareto lift charts, methods for handling large-sized, streaming and imbalanced data, support vector machines, and extended coverage of textual data mining. The second edition contains tutorials for attribute selection, dealing with imbalanced data, outlier analysis, time series analysis, mining textual data, and more.
The text provides in-depth coverage of RapidMiner Studio and Weka's Explorer interface. Both software tools are used for stepping students through the tutorials depicting the knowledge discovery process. This allows the reader maximum flexibility for their hands-on data mining experience.
目次
Data Mining: A First View. Data Mining: A Closer Look. Basic Data Mining Techniques. Weka - A Tool for Knowledge Discovery.
Pre Processing & Visualization Techniques. Knowledge Discovery in Databases. Formal Evaluation Techniques. The Data
Warehouse. Neural Networks. Building Neural Networks with BpKNet. Statistical Methods. Specialized Techniques. A Case Study
in Knowledge Discovery. Rule-Based Systems. Managing Uncertainty in Rule-Based Systems. Intelligent Agents
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