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8 produkter
8 produkter
1 479 kr
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This book gathers together much of the author’s work – both old and new - to explore a number of the key increases in complexity seen in the natural world, seeking to explain each of them purely in terms of the features of fitness landscapes.
1 479 kr
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This book gathers together much of the author’s work – both old and new - to explore a number of the key increases in complexity seen in the natural world, seeking to explain each of them purely in terms of the features of fitness landscapes.
Del 150 - Studies in Fuzziness and Soft Computing
Applications of Learning Classifier Systems
Inbunden, Engelska, 2004
1 632 kr
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This carefully edited book brings together a fascinating selection of applications of Learning Classifier Systems (LCS). The book demonstrates the utility of this machine learning technique in recent real-world applications in such domains as data mining, modelling and optimization, and control. It shows how the LCS technique combines and exploits many Soft Computing approaches into a single coherent framework to produce an improved performance over other approaches.
1 632 kr
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This volume brings together recent theoretical work in Learning Classifier Systems (LCS), which is a Machine Learning technique combining Genetic Algorithms and Reinforcement Learning. It includes self-contained background chapters on related fields (reinforcement learning and evolutionary computation) tailored for a classifier systems audience and written by acknowledged authorities in their area - as well as a relevant historical original work by John Holland.
Del 125 - Studies in Computational Intelligence
Learning Classifier Systems in Data Mining
Inbunden, Engelska, 2008
1 632 kr
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Just over thirty years after Holland first presented the outline for Learning Classifier System paradigm, the ability of LCS to solve complex real-world problems is becoming clear. In particular, their capability for rule induction in data mining has sparked renewed interest in LCS. This book brings together work by a number of individuals who are demonstrating their good performance in a variety of domains. The first contribution is arranged as follows: Firstly, the main forms of LCS are described in some detail. A number of historical uses of LCS in data mining are then reviewed before an overview of the rest of the volume is presented. The rest of this book describes recent research on the use of LCS in the main areas of machine learning data mining: classification, clustering, time-series and numerical prediction, feature selection, ensembles, and knowledge discovery.
Del 183 - Studies in Fuzziness and Soft Computing
Foundations of Learning Classifier Systems
Häftad, Engelska, 2010
1 584 kr
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This volume brings together recent theoretical work in Learning Classifier Systems (LCS), which is a Machine Learning technique combining Genetic Algorithms and Reinforcement Learning. It includes self-contained background chapters on related fields (reinforcement learning and evolutionary computation) tailored for a classifier systems audience and written by acknowledged authorities in their area - as well as a relevant historical original work by John Holland.
Del 125 - Studies in Computational Intelligence
Learning Classifier Systems in Data Mining
Häftad, Engelska, 2010
1 584 kr
Skickas inom 10-15 vardagar
Just over thirty years after Holland first presented the outline for Learning Classifier System paradigm, the ability of LCS to solve complex real-world problems is becoming clear. In particular, their capability for rule induction in data mining has sparked renewed interest in LCS. This book brings together work by a number of individuals who are demonstrating their good performance in a variety of domains. The first contribution is arranged as follows: Firstly, the main forms of LCS are described in some detail. A number of historical uses of LCS in data mining are then reviewed before an overview of the rest of the volume is presented. The rest of this book describes recent research on the use of LCS in the main areas of machine learning data mining: classification, clustering, time-series and numerical prediction, feature selection, ensembles, and knowledge discovery.
Del 150 - Studies in Fuzziness and Soft Computing
Applications of Learning Classifier Systems
Häftad, Engelska, 2012
1 584 kr
Skickas inom 10-15 vardagar
The field called Learning Classifier Systems is populated with romantics. Why shouldn't it be possible for computer programs to adapt, learn, and develop while interacting with their environments? In particular, why not systems that, like organic populations, contain competing, perhaps cooperating, entities evolving together? John Holland was one of the earliest scientists with this vision, at a time when so-called artificial intelligence was in its infancy and mainly concerned with preprogrammed systems that didn't learn. that, like organisms, had sensors, took Instead, Holland envisaged systems actions, and had rich self-generated internal structure and processing. In so doing he foresaw and his work prefigured such present day domains as reinforcement learning and embedded agents that are now displacing the older "standard Af' . One focus was what Holland called "classifier systems": sets of competing rule like "classifiers", each a hypothesis as to how best to react to some aspect of the environment--or to another rule. The system embracing such a rule "popu lation" would explore its available actions and responses, rewarding and rating the active rules accordingly. Then "good" classifiers would be selected and re produced, mutated and even crossed, a la Darwin and genetics, steadily and reliably increasing the system's ability to cope.