ECML-PKDD 1993

41 papers

A Note on Refinement Operators Tim Niblett

An Application of Machine Learning in the Domain of Loan Analysis José Luís Ferreira, Joaquim Correia, Thomas Jamet, Ernesto Costa

An Iterative and Bottom-up Procedure for Proving-by-Example Masami Hagiya

An Overview of Evolutionary Computation William M. Spears, Kenneth A. De Jong, Thomas Bäck, David B. Fogel, Hugo de Garis

Bayes and Pseudo-Bayes Estimates of Conditional Probabilities and Their Reliability James Cussens

Can Complexity Theory Benefit from Learning Theory? Tibor Hegedüs

COBBIT - A Control Procedure for COBWEB in the Presence of Concept Drift Fredrik Kilander, Carl Gustaf Jansson

Complexity Dimensions and Learnability Shan-Hwei Nienhuys-Cheng, Mark Polman

Controlled Redundancy in Incremental Rule Learning Luís Torgo

Decision Tree Pruning as a Search in the State Space Floriana Esposito, Donato Malerba, Giovanni Semeraro

Discovering Patterns in EEG-Signals: Comparative Study of a Few Methods Miroslav Kubat, Doris Flotzinger, Gert Pfurtscheller

Effective Learning in Dynamic Environments by Explicit Context Tracking Gerhard Widmer, Miroslav Kubat

Exploiting Context When Learning to Classify Peter D. Turney

Extraction of Knowledge from Data Using Constrained Neural Networks Raqui Kane, Irina Tchoumatchenko, Maurice Milgram

Feature Selection Using Rough Sets Theory Maciej Modrzejewski

FOIL: A Midterm Report J. Ross Quinlan, R. Mike Cameron-Jones

Funtional Inductive Logic Programming with Queries to the User Francesco Bergadano, Daniele Gunetti

Generalization Under Implication by Using Or-Introduction Peter Idestam-Almquist

Genetic Algorithms for Protein Tertiary Structure Prediction Steffen Schulze-Kremer

Getting Order Independence in Incremental Learning Antoine Cornuéjols

IDDD: An Inductive, Domain Dependent Decision Algorithm Lena Gaga, Vassilis Moustakis, Giorgos Charissis, Stelios C. Orphanoudakis

Improving Example-Guided Unfolding Henrik Boström

Induction of Recursive Bayesian Classifiers Pat Langley

Inductive Logic Programming: Derivations, Successes and Shortcomings Stephen H. Muggleton

Integrated Learning Architectures Enric Plaza, Agnar Aamodt, Ashwin Ram, Walter Van de Velde, Maarten van Someren

Integrating Models of Knowledge and Machine Learning Jean-Gabriel Ganascia, Jérôme Thomas, Philippe Laublet

Learnability of Constrained Logic Programs Saso Dzeroski, Stephen H. Muggleton, Stuart Russell

Learning Domain Theories Using Abstract Beckground Knowledge Peter Clark, Stan Matwin

Learning to Control Dynamic Systems with Automatic Quantization Charles X. Ling, Ralph Buchal

ML Techniques and Text Analysis Pieter W. Adriaans

On the Proper Definition of Minimality in Specialization and Theory Revision Stefan Wrobel

Predicate Invention in ILP - An Overview Irene Stahl

Predicate Invention in Inductive Data Engineering Peter A. Flach

Refinement of Rule Sets with JoJo Dieter Fensel, Markus Wiese

Rule Combination in Inductive Learning Luís Torgo

SAMIA: A Bottom-up Learning Method Using a Simulated Annealing Algorithm Pierre Brézellec, Henry Soldano

SIA: A Supervised Inductive Algorithm with Genetic Search for Learning Attributes Based Concepts Gilles Venturini

Some Lower Bounds for the Computational Complexity of Inductive Logic Programming Jörg-Uwe Kietz

Subsumption and Refinement in Model Inference Patrick R. J. van der Laag, Shan-Hwei Nienhuys-Cheng

Two Methods for Improving Inductive Logic Programming Systems Irene Stahl, Birgit Tausend, Rüdiger Wirth

Using Heuristics to Speed up Induction on Continuous-Valued Attributes Günter Seidelmann