Machine Learning: ECML-94 European Conference on Machine Learning, Catania, Italy, April 6-8, 1994. Proceedings

This volume contains the proceedings of the European Conference on Machine Learning 1994, which continues the tradition of earlier meetings and which is a major forum for the presentation of the latest and most significant results in machine learning. Machine learning is one of the most important su...

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Bibliographic Details
Other Authors: Bergadano, Francesco (Editor), Raedt, Luc de (Editor)
Format: eBook
Published: Berlin, Heidelberg Springer Berlin Heidelberg 1994, 1994
Edition:1st ed. 1994
Series:Lecture Notes in Artificial Intelligence
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
Table of Contents:
  • Learning belief network structure from data under causal insufficiency
  • Cost-sensitive pruning of decision trees
  • An instance-based learning method for databases: An information theoretic approach
  • Early screening for gastric cancer using machine learning techniques
  • DP1: Supervised and unsupervised clustering
  • Using machine learning techniques to interpret results from discrete event simulation
  • Flexible integration of multiple learning methods into a problem solving architecture
  • Concept sublattices
  • The piecewise linear classifier DIPOL92
  • Complexity of computing generalized VC-dimensions
  • Learning relations without closing the world
  • Properties of Inductive Logic Programming in function-free Horn logic
  • Representing biases for Inductive Logic Programming
  • Biases and their effects in Inductive Logic Programming
  • Inductive learning of normal clauses
  • Industrial applications of ML: Illustrations for the KAML dilemma and the CBR dream
  • Knowledge representation in machine learning
  • Inverting implication with small training sets
  • A context similarity measure
  • Incremental learning of control knowledge for nonlinear problem solving
  • Characterizing the applicability of classification algorithms using meta-level learning
  • Inductive learning of characteristic concept descriptions from small sets of classified examples
  • FOSSIL: A robust relational learner
  • A multistrategy learning system and its integration into an interactive floorplanning tool
  • Bottom-up induction of oblivious read-once decision graphs
  • Estimating attributes: Analysis and extensions of RELIEF
  • BMWk revisited generalization and formalization of an algorithm for detecting recursive relations in term sequences
  • An analytic and empirical comparison of two methods for discovering probabilistic causal relationships
  • Sample PAC-learnability in model inference
  • Averaging over decision stumps
  • Controlling constructive induction in CIPF: An MDL approach
  • Using constraints to building version spaces
  • On the utility of predicate invention in inductive logic programming
  • Learning problem-solving concepts by reflecting on problem solving
  • Existence and nonexistence of complete refinement operators
  • A hybrid nearest-neighbor and nearest-hyperrectangle algorithm
  • Automated knowledge acquisition for Prospector-like expert systems
  • On the role of machine learning in knowledge-based control
  • Discovering dynamics with genetic programming
  • A geometric approach to feature selection
  • Identifying unrecognizable regular languages by queries
  • Intensional learning of logic programs
  • Partially isomorphic generalization and analogical reasoning
  • Learning from recursive, tree structured examples
  • Concept formation in complex domains
  • An algorithm for learning hierarchical classifiers