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ORCIDAdvances in Machine Learning I 2010
- Jacek Koronacki, Zbigniew W. Ras, Slawomir T. Wierzchon
, Janusz Kacprzyk:
Advances in Machine Learning I: Dedicated to the Memory of Professor Ryszard S. Michalski. Studies in Computational Intelligence 262, Springer 2010, ISBN 978-3-642-05176-0
Introductory Chapters
- Janusz Wojtusiak, Kenneth A. Kaufman:
Ryszard S. Michalski: The Vision and Evolution of Machine Learning. 3-22 - Marcus A. Maloof:
The AQ Methods for Concept Drift. 23-47 - Krzysztof J. Cios, Lukasz A. Kurgan:
Machine Learning Algorithms Inspired by the Work of Ryszard Spencer Michalski. 49-74 - Janusz Kacprzyk, Grazyna Szkatula:
Inductive Learning: A Combinatorial Optimization Approach. 75-93
General Issues
- Pinar Donmez, Jaime G. Carbonell:
From Active to Proactive Learning Methods. 97-120 - Nada Lavrac, Johannes Fürnkranz, Dragan Gamberger:
Explicit Feature Construction and Manipulation for Covering Rule Learning Algorithms. 121-146 - Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin:
Transfer Learning via Advice Taking. 147-170
Classification and Beyond
- Pavel Brazdil, Rui Leite:
Determining the Best Classification Algorithm with Recourse to Sampling and Metalearning. 173-188 - Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Transductive Learning for Spatial Data Classification. 189-207 - Krzysztof Dembczynski, Wojciech Kotlowski, Roman Slowinski:
Beyond Sequential Covering - Boosted Decision Rules. 209-225 - Matti Saarela, Tapio Elomaa, Keijo Ruohonen:
An Analysis of Relevance Vector Machine Regression. 227-246 - Zbigniew W. Ras, Agnieszka Dardzinska, Wenxin Jiang:
Cascade Classifiers for Hierarchical Decision Systems. 247-256 - Gisele L. Pappa, Alex Alves Freitas:
Creating Rule Ensembles from Automatically-Evolved Rule Induction Algorithms. 257-273 - Ugo Galassi, Marco Botta, Lorenza Saitta:
Structured Hidden Markov Model versus String Kernel Machines for Symbolic Sequence Classification. 275-295
Soft Computing
- Ronald R. Yager:
Partition Measures for Data Mining. 299-319 - Jens Christian Hühn, Eyke Hüllermeier:
An Analysis of the FURIA Algorithm for Fuzzy Rule Induction. 321-344 - Jerzy W. Grzymala-Busse, Witold J. Grzymala-Busse:
Increasing Incompleteness of Data Sets - A Strategy for Inducing Better Rule Sets. 345-365 - Yaile Caballero, Rafael Bello, Leticia Arco, María M. García, Enislay Ramentol:
Knowledge Discovery Using Rough Set Theory. 367-383 - Aboul Ella Hassanien, Hameed Al-Qaheri, Václav Snásel, James F. Peters:
Machine Learning Techniques for Prostate Ultrasound Image Diagnosis. 385-403 - Marek Kowal, Józef Korbicz:
Segmentation of Breast Cancer Fine Needle Biopsy Cytological Images Using Fuzzy Clustering. 405-417
Machine Learning for Robotics
- Reinaldo A. C. Bianchi, Arnau Ramisa, Ramón López de Mántaras:
Automatic Selection of Object Recognition Methods Using Reinforcement Learning. 421-439 - Ivan Bratko:
Comparison of Machine Learning for Autonomous Robot Discovery. 441-456 - Claude Sammut, Tak Fai Yik:
Multistrategy Learning for Robot Behaviours. 457-476
Neural Networks and Other Nature Inspired Approaches
- Joachim Diederich, Alan B. Tickle, Shlomo Geva:
Quo Vadis? Reliable and Practical Rule Extraction from Neural Networks. 479-490 - Vladimir G. Red'ko, Danil V. Prokhorov:
Learning and Evolution of Autonomous Adaptive Agents. 491-500 - Alexander A. Frolov, Dusan Húsek, Igor P. Muraviev, Pavel Yu. Polyakov:
Learning and Unlearning in Hopfield-Like Neural Network Performing Boolean Factor Analysis. 501-518
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