By Richard J. Roiger
Data Mining: A Tutorial-Based Primer, moment Edition presents a entire creation to facts mining with a spotlight on version development and checking out, in addition to on analyzing and validating effects. The textual content courses scholars to appreciate how information mining will be hired to resolve actual difficulties and realize even if an information mining resolution is a possible substitute for a particular challenge. primary information mining suggestions, concepts, and evaluate tools are awarded and applied with assistance from recognized software program instruments.
Several new issues were extra to the second one version together with an advent to special facts and information analytics, ROC curves, Pareto carry charts, equipment for dealing with large-sized, streaming and imbalanced info, help vector machines, and prolonged assurance of textual info mining. the second one variation comprises tutorials for characteristic choice, facing imbalanced facts, outlier research, time sequence research, mining textual facts, and more.
The textual content offers in-depth insurance of RapidMiner Studio and Weka’s Explorer interface. either software program instruments are used for stepping scholars in the course of the tutorials depicting the information discovery procedure. this enables the reader greatest flexibility for his or her hands-on info mining experience.
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Facts Mining: A Tutorial-Based Primer, moment variation offers a complete creation to facts mining with a spotlight on version development and trying out, in addition to on studying and validating effects. The textual content publications scholars to appreciate how information mining should be hired to resolve genuine difficulties and realize even if an information mining resolution is a possible substitute for a selected challenge.
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Extra info for Data Mining: A Tutorial-Based Primer, Second Edition (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Data Mining: A Tutorial-Based Primer, Second Edition (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) by Richard J. Roiger