Theories for mutagenicity: a study in first-order and feature-based induction
Artificial Intelligence - Special volume on empirical methods
Relational learning with statistical predicate invention: better models for hypertext
Machine Learning - Special issue on inducive logic programming
Learning Logical Definitions from Relations
Machine Learning
Lookahead and Discretization in ILP
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Maximum Entropy Modeling with Clausal Constraints
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Simple Estimators for Relational Bayesian Classifiers
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Statistical Relational Learning for Document Mining
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
ACM SIGKDD Explorations Newsletter
Learning Bayesian network classifiers by maximizing conditional likelihood
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Naive Bayesian Classification of Structured Data
Machine Learning
Learning Bayesian networks of rules with SAYU
MRDM '05 Proceedings of the 4th international workshop on Multi-relational mining
Integrating Naïve Bayes and FOIL
The Journal of Machine Learning Research
An integrated approach to feature invention and model construction for drug activity prediction
Proceedings of the 24th international conference on Machine learning
k-RNN: k-relational nearest neighbour algorithm
Proceedings of the 2008 ACM symposium on Applied computing
Discriminative Structure Learning of Markov Logic Networks
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Towards Machine Learning on the Semantic Web
Uncertainty Reasoning for the Semantic Web I
An Inductive Logic Programming Approach to Statistical Relational Learning
Proceedings of the 2005 conference on An Inductive Logic Programming Approach to Statistical Relational Learning
kFOIL: learning simple relational kernels
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Change of representation for statistical relational learning
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Probabilistic inductive logic programming
Probabilistic inductive logic programming
Learning with kernels and logical representations
Probabilistic inductive logic programming
CLP(BN): constraint logic programming for probabilistic knowledge
Probabilistic inductive logic programming
Sequential pattern mining in multi-relational datasets
CAEPIA'09 Proceedings of the Current topics in artificial intelligence, and 13th conference on Spanish association for artificial intelligence
Boosting learning and inference in Markov logic through metaheuristics
Applied Intelligence
Toward robust real-world inference: a new perspective on explanation-based learning
ECML'06 Proceedings of the 17th European conference on Machine Learning
Fisher kernels for relational data
ECML'06 Proceedings of the 17th European conference on Machine Learning
Statistical relational learning: an inductive logic programming perspective
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Statistical relational learning: an inductive logic programming perspective
ECML'05 Proceedings of the 16th European conference on Machine Learning
An integrated approach to learning bayesian networks of rules
ECML'05 Proceedings of the 16th European conference on Machine Learning
Automatic traffic incident detection based on nFOIL
Expert Systems with Applications: An International Journal
Relational Feature Mining with Hierarchical Multitask kFOIL
Fundamenta Informaticae - Machine Learning in Bioinformatics
Subgroup discovery using bump hunting on multi-relational histograms
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
Conceptual clustering of multi-relational data
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
A new relational Tri-training system with adaptive data editing for inductive logic programming
Knowledge-Based Systems
Transforming graph data for statistical relational learning
Journal of Artificial Intelligence Research
Simple decision forests for multi-relational classification
Decision Support Systems
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We present the system nFOIL. It tightly integrates the naïve Bayes learning scheme with the inductive logic programming rule-learner FOIL. In contrast to previous combinations, which have employed naïve Bayes only for post-processing the rule sets, nFOIL employs the naïve Bayes criterion to directly guide its search. Experimental evidence shows that nFOIL performs better than both its base line algorithm FOIL or the post-processing approach, and is at the same time competitive with more sophisticated approaches.