By Zhi-Hua Zhou
An up to date, self-contained creation to a state of the art desktop studying procedure, Ensemble tools: Foundations and Algorithms indicates how those exact tools are utilized in real-world projects. It provides the mandatory foundation to hold out extra examine during this evolving field.
After offering heritage and terminology, the e-book covers the most algorithms and theories, together with Boosting, Bagging, Random woodland, averaging and vote casting schemes, the Stacking process, mix of specialists, and variety measures. It additionally discusses multiclass extension, noise tolerance, error-ambiguity and bias-variance decompositions, and up to date growth in info theoretic diversity.
Moving directly to extra complicated subject matters, the writer explains how you can in achieving greater functionality via ensemble pruning and the way to generate higher clustering effects via combining a number of clusterings. furthermore, he describes advancements of ensemble equipment in semi-supervised studying, energetic studying, cost-sensitive studying, class-imbalance studying, and comprehensibility enhancement.
Read or Download Ensemble Methods: Foundations and Algorithms (Chapman & Hall/CRC Data Mining and Knowledge Discovery Serie) PDF
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Additional resources for Ensemble Methods: Foundations and Algorithms (Chapman & Hall/CRC Data Mining and Knowledge Discovery Serie)
Ensemble Methods: Foundations and Algorithms (Chapman & Hall/CRC Data Mining and Knowledge Discovery Serie) by Zhi-Hua Zhou