Part-of-Speech Tagging Using Decision Trees
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Experiments on Solving Multiclass Learning Problems by n2-classifier
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Part-of-Speech Tagging Using Progol
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Inducing Shogi Heuristics Using Inductive Logic Programming
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Using Prior Probabilities and Density Estimation for Relational Classification
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Maximum Entropy Modeling with Clausal Constraints
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Combining Statistical and Relational Methods for Learning in Hypertext Domains
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
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This paper defines a selection problem where an appropriate object is selected from a set that is specified by parameters. We discuss inductive learning of selection problems and proposed a method combining inductive logic programming (ILP) and Bayesian learning. Our methods estimate probability of each choice by evaluating likelihood of an induced relation from an ideal binary relation. Bayesian learning combines a prior probability of objects and the estimated probability. By making several assumptions on probability estimation, we give several methods. The methods are applied to Part-of-Speech tagging.