Machine Learning Proceedings 1992
Author: Peter Edwards
Publisher: Morgan Kaufmann
Published: 2014-06-28
Total Pages: 497
ISBN-13: 1483298531
DOWNLOAD EBOOKMachine Learning Proceedings 1992
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Author: Peter Edwards
Publisher: Morgan Kaufmann
Published: 2014-06-28
Total Pages: 497
ISBN-13: 1483298531
DOWNLOAD EBOOKMachine Learning Proceedings 1992
Author: Derek Sleeman
Publisher:
Published: 2014
Total Pages: 0
ISBN-13:
DOWNLOAD EBOOKMachine Learning Proceedings 1992.
Author: J. Ross Quinlan
Publisher: Morgan Kaufmann
Published: 1993
Total Pages: 286
ISBN-13: 9781558602380
DOWNLOAD EBOOKThis book is a complete guide to the C4.5 system as implemented in C for the UNIX environment. It contains a comprehensive guide to the system's use, the source code (about 8,800 lines), and implementation notes.
Author: Derek Sleeman
Publisher:
Published: 1992
Total Pages:
ISBN-13: 9781558602472
DOWNLOAD EBOOKAuthor: Lawrence A. Birnbaum
Publisher: Morgan Kaufmann
Published: 2014-05-23
Total Pages: 361
ISBN-13: 1483298620
DOWNLOAD EBOOKMachine Learning Proceedings 1993
Author: A Adams
Publisher: World Scientific
Published: 1992-10-09
Total Pages: 410
ISBN-13: 9814553603
DOWNLOAD EBOOKThe papers in this volume deal with academic research topics as well as practical applications in AI. Special emphasis is given to computer vision, machine learning, neural networks mixed with theory of logic and reasoning, and practical applications of expert systems in industry and decision support.
Author: William W. Cohen
Publisher: Morgan Kaufmann
Published: 2014-06-28
Total Pages: 398
ISBN-13: 1483298183
DOWNLOAD EBOOKMachine Learning Proceedings 1994
Author: Armand Prieditis
Publisher: Morgan Kaufmann
Published: 2014-06-28
Total Pages: 606
ISBN-13: 1483298663
DOWNLOAD EBOOKMachine Learning Proceedings 1995
Author: Anthony Adams
Publisher: World Scientific Publishing Company Incorporated
Published: 1992-01-01
Total Pages: 396
ISBN-13: 9789810212506
DOWNLOAD EBOOKAuthor: Stephen J. Hanson
Publisher: Springer Science & Business Media
Published: 1993-03-30
Total Pages: 292
ISBN-13: 9783540564836
DOWNLOAD EBOOKThis volume includes some of the key research papers in the area of machine learning produced at MIT and Siemens during a three-year joint research effort. It includes papers on many different styles of machine learning, organized into three parts. Part I, theory, includes three papers on theoretical aspects of machine learning. The first two use the theory of computational complexity to derive some fundamental limits on what isefficiently learnable. The third provides an efficient algorithm for identifying finite automata. Part II, artificial intelligence and symbolic learning methods, includes five papers giving an overview of the state of the art and future developments in the field of machine learning, a subfield of artificial intelligence dealing with automated knowledge acquisition and knowledge revision. Part III, neural and collective computation, includes five papers sampling the theoretical diversity and trends in the vigorous new research field of neural networks: massively parallel symbolic induction, task decomposition through competition, phoneme discrimination, behavior-based learning, and self-repairing neural networks.