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Incremental Learning in Intelligent Systems

By (author) Seiichi Ozawa, By (author) Shaoning Pang, By (author) Nikola Kasabov

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Part of the IEEE series on Computational Intelligence, this book offers the first text to cover both single task and multiple task incremental learning. The broad coverage encompasses both incremental learning theories and practical applications including pattern recognition, time-series prediction, outlier detection, adaptive robotics, bioinformatics, and biomedical diagnosis. Providing readers across multiple disciplines with a common foundation to work from, this book will prove an essential resource in efforts to develop new learning theories and algorithms, and in building new types of intelligent systems.

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