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

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...

Full description

Bibliographic Details
Other Authors: Someren, Maarten van (Editor), Widmer, Gerhard (Editor)
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 1997, 1997
Edition:1st ed. 1997
Series:Lecture Notes in Artificial Intelligence
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
LEADER 03621nmm a2200325 u 4500
001 EB000659423
003 EBX01000000000000000512505
005 00000000000000.0
007 cr|||||||||||||||||||||
008 140122 ||| eng
020 |a 9783540687085 
100 1 |a Someren, Maarten van  |e [editor] 
245 0 0 |a Machine Learning: ECML'97  |h Elektronische Ressource  |b 9th European Conference on Machine Learning, Prague, Czech Republic, April 23 - 25, 1997, Proceedings  |c edited by Maarten van Someren, Gerhard Widmer 
250 |a 1st ed. 1997 
260 |a Berlin, Heidelberg  |b Springer Berlin Heidelberg  |c 1997, 1997 
300 |a XIV, 366 p  |b online resource 
505 0 |a 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 --  
505 0 |a Learning in dynamically changing domains: Theory revision and context dependence issues 
505 0 |a Inductive Genetic Programming with Decision Trees -- Parallel anddistributed 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 --  
653 |a Artificial Intelligence 
653 |a Algorithms 
653 |a Artificial intelligence 
700 1 |a Widmer, Gerhard  |e [editor] 
041 0 7 |a eng  |2 ISO 639-2 
989 |b SBA  |a Springer Book Archives -2004 
490 0 |a Lecture Notes in Artificial Intelligence 
028 5 0 |a 10.1007/3-540-62858-4 
856 4 0 |u https://doi.org/10.1007/3-540-62858-4?nosfx=y  |x Verlag  |3 Volltext 
082 0 |a 006.3 
520 |a 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 to the invited talks as well as descriptions from four satellite workshops. The volume covers the whole spectrum of current machine learning issues