Background
Abe, Shigeo was born on June 19, 1947 in Matsuyama, Ehime, Japan. Son of Rihei and Masuko Abe.
(This book provides a unified approach for developing a fu...)
This book provides a unified approach for developing a fuzzy classifier and explains the advantages and disadvantages of different classifiers through extensive performance evaluation of real data sets. It thus offers new learning paradigms for analyzing neural networks and fuzzy systems, while training fuzzy classifiers. Function approximation is also treated and function approximators are compared.
http://www.amazon.com/gp/product/1852333529/?tag=2022091-20
( A guide on the use of SVMs in pattern classification, i...)
A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empirical feature space, and the effect of model selection by cross-validation; Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Explores incremental training based batch training and active-set training methods, and decomposition techniques for linear programming SVMs; Discusses variable selection for support vector regressors.
http://www.amazon.com/gp/product/1849960976/?tag=2022091-20
(This guide on the use of SVMs in pattern classification i...)
This guide on the use of SVMs in pattern classification includes a rigorous performance comparison of classifiers and regressors. The book takes the unique approach of focusing on classification rather than covering the theoretical aspects of SVMs.
http://www.amazon.com/gp/product/1447125487/?tag=2022091-20
(Support vector machines (SVMs), were originally formulate...)
Support vector machines (SVMs), were originally formulated for two-class classification problems, and have been accepted as a powerful tool for developing pattern classification and function approximations systems. This book provides a unique perspective of the state of the art in SVMs by taking the only approach that focuses on classification rather than covering the theoretical aspects. The book clarifies the characteristics of two-class SVMs through their extensive analysis, presents various useful architectures for multiclass classification and function approximation problems, and discusses kernel methods for improving generalization ability of conventional neural networks and fuzzy systems. Ample illustrations, examples and computer experiments are included to help readers understand the new ideas and their usefulness. This book supplies a comprehensive resource for the use of SVMs in pattern classification and will be invaluable reading for researchers, developers & students in academia and industry.
http://www.amazon.com/gp/product/1852339292/?tag=2022091-20
(Neural Networks and Fuzzy Systems: Theory and Application...)
Neural Networks and Fuzzy Systems: Theory and Applications discusses theories that have proven useful in applying neural networks and fuzzy systems to real world problems. The book includes performance comparison of neural networks and fuzzy systems using data gathered from real systems. Topics covered include the Hopfield network for combinatorial optimization problems, multilayered neural networks for pattern classification and function approximation, fuzzy systems that have the same functions as multilayered networks, and composite systems that have been successfully applied to real world problems. The author also includes representative neural network models such as the Kohonen network and radial basis function network. New fuzzy systems with learning capabilities are also covered. The advantages and disadvantages of neural networks and fuzzy systems are examined. The performance of these two systems in license plate recognition, a water purification plant, blood cell classification, and other real world problems is compared.
http://www.amazon.com/gp/product/1461378699/?tag=2022091-20
Abe, Shigeo was born on June 19, 1947 in Matsuyama, Ehime, Japan. Son of Rihei and Masuko Abe.
Bachelor of Science in Electrical Engineering, Kyoto University, Japan, 1970. Master of Science in Electrical Engineering, Kyoto University, Japan, 1972. Doctor of Engineering, Kyoto University, Japan, 1984.
Researcher, Hitachi (Japan) Research Laboratory, Hitachi, Ltd., 1972-1984; senior researcher, Hitachi (Japan) Research Laboratory, Hitachi, Ltd., 1984-1993; chief researcher, Hitachi (Japan) Research Laboratory, Hitachi, Ltd., 1993-1997; professor, Kobe (Japan) U., since 1997. Visiting research associate University Texas, Arlington, 1978-1979.
(Support vector machines (SVMs), were originally formulate...)
(This book provides a unified approach for developing a fu...)
(Neural Networks and Fuzzy Systems: Theory and Application...)
(This guide on the use of SVMs in pattern classification i...)
( A guide on the use of SVMs in pattern classification, i...)
Member Institute of Electrical and Electronics Engineers (senior), Institute Elec. Engineers Japan (Outstanding Paper prize 1984, 95), Information Processing Society Japan, International Neural Network Society, Institute Electronics, Information and Comm. Engineers, The Society Instrument and Control Engineers.
Married Yoshiko Izumi, May 5, 1973. Children: Takuya, Michiru, Masaya.