Machine learning and its applications

Machine Learning and Its Applications: Advanced Lectures
Author: Georgios Paliouras, Vangelis Karkaletsis, Constantine D. Spyropoulos
Published by Springer Berlin Heidelberg
ISBN: 978-3-540-42490-1
DOI: 10.1007/3-540-44673-7

Table of Contents:

• Comparing Machine Learning and Knowledge Discovery in DataBases: An Application to Knowledge Discovery in Texts
• Learning Patterns in Noisy Data: The AQ Approach
• Unsupervised Learning of Probabilistic Concept Hierarchies
• Function Decomposition in Machine Learning
• How to Upgrade Propositional Learners to First Order Logic: A Case Study
• Case-Based Reasoning
• Genetic Algorithms in Machine Learning
• Pattern Recognition and Neural Networks
• Model Class Selection and Construction: Beyond the Procrustean Approach to Machine Learning Applications
• Integrated Architectures for Machine Learning
• The Computational Support of Scientic Discovery
• Support Vector Machines: Theory and Applications
• Pre- and Post-processing in Machine Learning and Data Mining
• Machine Learning in Human Language Technology
• Machine Learning for Intelligent Information Access
• Machine Learning and Intelligent Agents
• Machine Learning in User Modeling
• Data Mining in Economics, Finance, and Marketing
• Machine Learning in Medical Applications
• Machine Learning Applications to Power Systems