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The primary goal of this book is to give readers a complete treatment of the state-of-the-art ensemble learning methods, and provide a set of applications that demonstrate the various usages of ensemble learning methods in the real-world. For readers who are new to the subject, this book provides an excellent entry point with high-level introductory view of the topic as well as in-depth discussion of the key technical details. For researchers in the area, this book is a handy reference summarizing the up-to-date advances in ensemble learning, their connections, and future directions. For practitioners, the book provides a number of example applications for ensemble learning, and offers examples of successful, real-world systems.
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