Machine Learning: ECML'97 9th European Conference on Machine Learning, Prague, Czech Republic, April 23 - 25, 1997, Proceedings /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Someren, Maarten van (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Widmer, Gerhard (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1997.
• Έκδοση: 1st ed. 1997.
• Σειρά: Lecture Notes in Artificial Intelligence ; 1224
• Θέματα: Artificial intelligence.; Algorithms.; Artificial Intelligence.; Algorithm Analysis and Problem Complexity.

This book constitutes the refereed proceedings of the Ninth European Conference on Machine Learning, ECML-97, held in Prague, Czech Republic, in April 1997. This volume presents 26 revised full papers selected from a total of 73 submissions. Also included are an abstract and two papers corresponding...

Πίνακας περιεχομένων:

• Uncertain learning agents
• Constructing and sharing perceptual distinctions
• On prediction by data compression
• Induction of feature terms with INDIE
• Exploiting qualitative knowledge to enhance skill acquisition
• Integrated learning and planning based on truncating temporal differences
• ?-subsumption for structural matching
• Classification by Voting Feature Intervals
• Constructing intermediate concepts by decomposition of real functions
• Conditions for Occam's razor applicability and noise elimination
• Learning different types of new attributes by combining the neural network and iterative attribute construction
• Metrics on terms and clauses
• Learning when negative examples abound
• A model for generalization based on confirmatory induction
• Learning Linear Constraints in Inductive Logic Programming
• Finite-Element methods with local triangulation refinement for continuous reinforcement learning problems
• Inductive Genetic Programming with Decision Trees
• Parallel and distributed search for structure in multivariate time series
• Compression-based pruning of decision lists
• Probabilistic Incremental Program Evolution: Stochastic search through program space
• NeuroLinear: A system for extracting oblique decision rules from neural networks
• Inducing and using decision rules in the GRG knowledge discovery system
• Learning and exploitation do not conflict under minimax optimality
• Model combination in the multiple-data-batches scenario
• Search-based class discretization
• Natural ideal operators in Inductive Logic Programming
• A case study in loyalty and satisfaction research
• Ibots learn genuine team solutions
• Global data analysis and the fragmentation problem in decision tree induction
• Case-based learning: Beyond classification of feature vectors
• Empirical learning of Natural Language Processing tasks
• Human-Agent Interaction and Machine Learning
• Learning in dynamically changing domains: Theory revision and context dependence issues.