Machine Learning: ECML-98 : 10th European Conference on Machine Learning, Chemnitz, Germany, April 21-23, 1998, Proceedings / edited by Claire Nedellec, Celine Rouveirol.

Format:

Book

Contributor:

Nédellec, Claire, 1963- editor.

Rouveirol, Céline, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 1398.

Lecture Notes in Artificial Intelligence ; 1398

Language:

English

Subjects (All):

Artificial intelligence.

Algorithms.

Artificial Intelligence.

Algorithm Analysis and Problem Complexity.

Local Subjects:

Artificial Intelligence.

Algorithm Analysis and Problem Complexity.

Physical Description:

1 online resource (XIV, 426 pages).

Edition:

First edition 1998.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1998.

System Details:

text file PDF

Summary:

This book constitutes the refereed proceedings of the 10th European Conference on Machine Learning, ECML-98, held in Chemnitz, Germany, in April 1998. The book presents 21 revised full papers and 25 short papers reporting on work in progress together with two invited contributions; the papers were selected from a total of 100 submissions. The book is divided in sections on applications of ML, Bayesian networks, feature selection, decision trees, support vector learning, multiple models for classification, inductive logic programming, relational learning, instance-based learning, clustering, genetic algorithms, reinforcement learning and neural networks.

Contents:

Learning in agent-oriented worlds

Naive (Bayes) at forty: The independence assumption in information retrieval

Learning verbal transitivity using loglinear models

Part-of-speech tagging using decision trees

Inference of finite automata: Reducing the search space with an ordering of pairs of states

Automatic acquisition of lexical knowledge from sparse and noisy data

A normalization method for contextual data: Experience from a large-scale application

Learning to classify x-ray images using relational learning

ILP experiments in detecting traffic problems

Simulating children learning and explaining elementary heat transfer phenomena: A multistrategy system at work

Bayes optimal instance-based learning

Bayesian and information-theoretic priors for Bayesian network parameters

Feature subset selection in text-learning

A monotonic measure for optimal feature selection

Inducing models of human control skills

God doesn't always shave with Occam's razor - Learning when and how to prune

Error estimators for pruning regression trees

Pruning decision trees with misclassification costs

Text categorization with Support Vector Machines: Learning with many relevant features

A short note about the application of polynomial kernels with fractional degree in Support Vector Learning

Classification learning using all rules

Improved pairwise coupling classification with correcting classifiers

Experiments on solving multiclass learning problems by n 2-classifier

Combining classifiers by constructive induction

Boosting trees for cost-sensitive classifications

Naive bayesian classifier committees

Batch classifications with discrete finite mixtures

Induction of recursive program schemes

Predicate invention and learning from positive examples only

An inductive logic programming framework to learn a concept from ambiguous examples

First-order learning for Web mining

Explanation-based generalization in game playing: Quantitative results

Scope classification: An instance-based learning algorithm with a rule-based characterisation

Error-correcting output codes for local learners

Recursive lazy learning for modeling and control

Using lattice-based framework as a tool for feature extraction

Determining property relevance in concept formation by computing correlation between properties

A buffering strategy to avoid ordering effects in clustering

Coevolutionary, distributed search for inducing concept descriptions

Continuous mimetic evolution

A host-parasite genetic algorithm for asymmetric tasks

Speeding up Q(?)-learning

Q-learning and redundancy reduction in classifier systems with internal state

Composing functions to speed up reinforcement learning in a changing world

Theoretical results on reinforcement learning with temporally abstract options

A general convergence method for Reinforcement Learning in the continuous case

Interpretable neural networks with BP-SOM

Convergence rate of minimization learning for neural networks.

Other Format:

Printed edition:

ISBN:

978-3-540-69781-7

9783540697817

Access Restriction:

Restricted for use by site license.