Rule induction with CN2: some recent improvements
EWSL-91 Proceedings of the European working session on learning on Machine learning
Evaluating text categorization
HLT '91 Proceedings of the workshop on Speech and Natural Language
Machine Learning
Theories for mutagenicity: a study in first-order and feature-based induction
Artificial Intelligence - Special volume on empirical methods
Machine Learning - Special issue on learning with probabilistic representations
Separate-and-Conquer Rule Learning
Artificial Intelligence Review
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Relational learning of pattern-match rules for information extraction
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Relational learning with statistical predicate invention: better models for hypertext
Machine Learning - Special issue on inducive logic programming
Machine Learning
Logic, Programming, and PROLOG
Logic, Programming, and PROLOG
Relational learning and boosting
Relational Data Mining
Learning Logical Definitions from Relations
Machine Learning
Machine Learning
Phase Transitions and Stochastic Local Search in k-Term DNF Learning
ECML '02 Proceedings of the 13th European Conference on Machine Learning
Using Rule Sets to Maximize ROC Performance
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
A Theory-Refinement Approach to Information Extraction
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Learning Probabilistic Relational Models
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
ILP '96 Selected Papers from the 6th International Workshop on Inductive Logic Programming
Statistical Relational Learning for Document Mining
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
Sources of Success for Boosted Wrapper Induction
The Journal of Machine Learning Research
Towards tight bounds for rule learning
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Machine Learning
The relationship between Precision-Recall and ROC curves
ICML '06 Proceedings of the 23rd international conference on Machine learning
nFOIL: integrating Naïve Bayes and FOIL
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Learning probabilities for noisy first-order rules
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Representing sentence structure in hidden Markov models for information extraction
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Comparative experiments on learning information extractors for proteins and their interactions
Artificial Intelligence in Medicine
An empirical evaluation of bagging in inductive logic programming
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
Lattice-search runtime distributions may be heavy-tailed
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
An integrated approach to learning bayesian networks of rules
ECML'05 Proceedings of the 16th European conference on Machine Learning
Combining clauses with various precisions and recalls to produce accurate probabilistic estimates
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
Using Bayesian networks to direct stochastic search in inductive logic programming
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
Boosting first-order clauses for large, skewed data sets
ILP'09 Proceedings of the 19th international conference on Inductive logic programming
Learning theories using estimation distribution algorithms and (reduced) bottom clauses
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
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It is well known that many hard tasks considered in machine learning and data mining can be solved in a rather simple and robust way with an instance- and distance-based approach. In this work we present another difficult task: learning, from large numbers ...