Innovations in Machine Learning: Theory and Applications: Studies in Fuzziness and Soft Computing, cartea 194
Editat de Dawn E. Holmesen Limba Engleză Hardback – 9 mar 2006
Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Postgraduate since it shows the direction of current research.
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Specificații
ISBN-13: 9783540306092
ISBN-10: 3540306099
Pagini: 296
Ilustrații: XVI, 276 p.
Dimensiuni: 155 x 235 x 22 mm
Greutate: 0.59 kg
Ediția:2006
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Fuzziness and Soft Computing
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3540306099
Pagini: 296
Ilustrații: XVI, 276 p.
Dimensiuni: 155 x 235 x 22 mm
Greutate: 0.59 kg
Ediția:2006
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Fuzziness and Soft Computing
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
A Bayesian Approach to Causal Discovery.- A Tutorial on Learning Causal Influence.- Learning Based Programming.- N-1 Experiments Suffice to Determine the Causal Relations Among N Variables.- Support Vector Inductive Logic Programming.- Neural Probabilistic Language Models.- Computational Grammatical Inference.- On Kernel Target Alignment.- The Structure of Version Space.
Textul de pe ultima copertă
Machine learning is currently one of the most rapidly growing areas of research in computer science. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. This book covers the three main learning systems; symbolic learning, neural networks and genetic algorithms as well as providing a tutorial on learning casual influences. Each of the nine chapters is self-contained.
Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Postgraduate since it shows the direction of current research.
Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Postgraduate since it shows the direction of current research.
Caracteristici
Latest research in machine learning