Advances in Machine Learning II

1. Classification and Beyond

   1. Simple Algorithms for Frequent Item Set Mining

      • Christian Borgelt

      Pages 351-369

   2. Monte Carlo Feature Selection and Interdependency Discovery in Supervised Classification

      • Michał Dramiński, Marcin Kierczak, Jacek Koronacki, Jan Komorowski

      Pages 371-385

   3. Machine Learning Methods in Automatic Image Annotation

      • Halina Kwaśnicka, Mariusz Paradowski

      Pages 387-411

2. Neural Networks and Other Nature Inspired Approaches

   1. Front Matter

      Pages 413-413

      PDF

   2. Integrative Probabilistic Evolving Spiking Neural Networks Utilising Quantum Inspired Evolutionary Algorithm: A Computational Framework

      • Nikola Kasabov

      Pages 415-425

   3. Machine Learning in Vector Models of Neural Networks

      • Boris Kryzhanovsky, Vladimir Kryzhanovsky, Leonid Litinskii

      Pages 427-443

   4. Nature Inspired Multi-Swarm Heuristics for Multi-Knowledge Extraction

      • Hongbo Liu, Ajith Abraham, Benxian Yue

      Pages 445-466

   5. Discovering Data Structures Using Meta-learning, Visualization and Constructive Neural Networks

      • Tomasz Maszczyk, Marek Grochowski, Włodzisław Duch

      Pages 467-484

   6. Neural Network and Artificial Immune Systems for Malware and Network Intrusion Detection

      • Vladimir Golovko, Sergei Bezobrazov, Pavel Kachurka, Leanid Vaitsekhovich

      Pages 485-513

   7. Immunocomputing for Speaker Recognition

      • Alexander O. Tarakanov

      Pages 515-529

3. Back Matter

   PDF

Professor Richard S. Michalski passed away on September 20, 2007. Once we learned about his untimely death we immediately realized that we would no longer have with us a truly exceptional scholar and researcher who for several decades had been inf- encing the work of numerous scientists all over the world - not only in his area of exp- tise, notably machine learning, but also in the broadly understood areas of data analysis, data mining, knowledge discovery and many others. In fact, his influence was even much broader due to his creative vision, integrity, scientific excellence and excepti- ally wide intellectual horizons which extended to history, political science and arts. Professor Michalski’s death was a particularly deep loss to the whole Polish sci- tific community and the Polish Academy of Sciences in particular. After graduation, he began his research career at the Institute of Automatic Control, Polish Academy of Science in Warsaw. In 1970 he left his native country and hold various prestigious positions at top US universities. His research gained impetus and he soon established himself as a world authority in his areas of interest – notably, he was widely cons- ered a father of machine learning.

• STATISTICA
• Web 2.0
• classification
• data analysis
• data mining
• evolutionary algorithm
• heuristics
• learning
• machine learning
• proving
• supervised learning
• unsupervised learning
• visualization
• web mining

• Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland

  Jacek Koronacki, Sławomir T. Wierzchoń

• Woodward Hall 430C, University of North Carolina, Charlotte, USA

  Zbigniew W. Raś

• Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

  Janusz Kacprzyk

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