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Metalearning
  • Language: en
  • Pages: 182

Metalearning

Metalearning is the study of principled methods that exploit metaknowledge to obtain efficient models and solutions by adapting machine learning and data mining processes. While the variety of machine learning and data mining techniques now available can, in principle, provide good model solutions, a methodology is still needed to guide the search for the most appropriate model in an efficient way. Metalearning provides one such methodology that allows systems to become more effective through experience. This book discusses several approaches to obtaining knowledge concerning the performance of machine learning and data mining algorithms. It shows how this knowledge can be reused to select, combine, compose and adapt both algorithms and models to yield faster, more effective solutions to data mining problems. It can thus help developers improve their algorithms and also develop learning systems that can improve themselves. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining and artificial intelligence.

Inductive Logic Programming
  • Language: en
  • Pages: 437

Inductive Logic Programming

  • Type: Book
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  • Published: 2005-08-29
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  • Publisher: Springer

1 “Change is inevitable.” Embracing this quote we have tried to carefully exp- iment with the format of this conference, the 15th International Conference on Inductive Logic Programming, hopefully making it even better than it already was. But it will be up to you, the inquisitive reader of this book, to judge our success. The major changes comprised broadening the scope of the conference to include more diverse forms of non-propositional learning, to once again have tutorials on exciting new areas, and, for the ?rst time, to also have a discovery challenge as a platform for collaborative work. This year the conference was co-located with ICML 2005, the 22nd Inter- tional Conference on M...

Principles of Data Mining and Knowledge Discovery
  • Language: en
  • Pages: 717

Principles of Data Mining and Knowledge Discovery

  • Type: Book
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  • Published: 2003-07-31
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  • Publisher: Springer

This book constitutes the refereed proceedings of the 4th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2000, held in Lyon, France in September 2000. The 86 revised papers included in the book correspond to the 29 oral presentations and 57 posters presented at the conference. They were carefully reviewed and selected from 147 submissions. The book offers topical sections on new directions, rules and trees, databases and reward-based learning, classification, association rules and exceptions, instance-based discovery, clustering, and time series analysis.

Foundations of Genetic Programming
  • Language: en
  • Pages: 265

Foundations of Genetic Programming

This is one of the only books to provide a complete and coherent review of the theory of genetic programming (GP). In doing so, it provides a coherent consolidation of recent work on the theoretical foundations of GP. A concise introduction to GP and genetic algorithms (GA) is followed by a discussion of fitness landscapes and other theoretical approaches to natural and artificial evolution. Having surveyed early approaches to GP theory it presents new exact schema analysis, showing that it applies to GP as well as to the simpler GAs. New results on the potentially infinite number of possible programs are followed by two chapters applying these new techniques.

Logic for Learning
  • Language: en
  • Pages: 263

Logic for Learning

This book provides a systematic approach to knowledge representation, computation, and learning using higher-order logic. For those interested in computational logic, it provides a framework for knowledge representation and computation based on higher-order logic, and demonstrates its advantages over more standard approaches based on first-order logic. For those interested in machine learning, the book explains how higher-order logic provides suitable knowledge representation formalisms and hypothesis languages for machine learning applications.

Managing Customer Relationships
  • Language: en
  • Pages: 460

Managing Customer Relationships

MANAGING CUSTOMER RELATIONSHIPS A Strategic Framework Praise for the first edition: "Peppers and Rogers do a beautiful job of integrating actionable frameworks, the thinking of other leaders in the field, and best practices from leading-edge companies. "—Dr. Hugh J. Watson, C. Herman and Mary Virginia Terry Chair of Business Administration, Terry College of Business, University of Georgia "Peppers and Rogers have been the vanguard for the developing field of customer relationship management, and in this book, they bring their wealth of experience and knowledge into academic focus. This text successfully centers the development of the field and its theories and methodologies squarely within...

Advanced Data Mining and Applications
  • Language: en
  • Pages: 1130

Advanced Data Mining and Applications

Here are the proceedings of the 2nd International Conference on Advanced Data Mining and Applications, ADMA 2006, held in Xi'an, China, August 2006. The book presents 41 revised full papers and 74 revised short papers together with 4 invited papers. The papers are organized in topical sections on association rules, classification, clustering, novel algorithms, multimedia mining, sequential data mining and time series mining, web mining, biomedical mining, advanced applications, and more.

Advances in Computational Intelligence and Learning
  • Language: en
  • Pages: 518

Advances in Computational Intelligence and Learning

Advances in Computational Intelligence and Learning: Methods and Applications presents new developments and applications in the area of Computational Intelligence, which essentially describes methods and approaches that mimic biologically intelligent behavior in order to solve problems that have been difficult to solve by classical mathematics. Generally Fuzzy Technology, Artificial Neural Nets and Evolutionary Computing are considered to be such approaches. The Editors have assembled new contributions in the areas of fuzzy sets, neural sets and machine learning, as well as combinations of them (so called hybrid methods) in the first part of the book. The second part of the book is dedicated to applications in the areas that are considered to be most relevant to Computational Intelligence.

Hybrid Neural Systems
  • Language: en
  • Pages: 411

Hybrid Neural Systems

  • Type: Book
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  • Published: 2006-12-30
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  • Publisher: Springer

Hybrid neural systems are computational systems which are based mainly on artificial neural networks and allow for symbolic interpretation or interaction with symbolic components. This book is derived from a workshop held during the NIPS'98 in Denver, Colorado, USA, and competently reflects the state of the art of research and development in hybrid neural systems. The 26 revised full papers presented together with an introductory overview by the volume editors have been through a twofold process of careful reviewing and revision. The papers are organized in the following topical sections: structured connectionism and rule representation; distributed neural architectures and language processing; transformation and explanation; robotics, vision, and cognitive approaches.

Proceedings of the Twenty-second Annual Conference of the Cognitive Science Society
  • Language: en
  • Pages: 1108

Proceedings of the Twenty-second Annual Conference of the Cognitive Science Society

Vol inclu all ppers & postrs presntd at 2000 Cog Sci mtg & summaries of symposia & invitd addresses. Dealg wth issues of representg & modelg cog procsses, appeals to scholars in all subdiscip tht comprise cog sci: psy, compu sci, neuro sci, ling, & philo