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SAINT
2005
IEEE
14 years 1 months ago
Inductive Logic Programming for Structure-Activity Relationship Studies on Large Scale Data
Inductive Logic Programming (ILP) is a combination of inductive learning and first-order logic aiming to learn first-order hypotheses from training examples. ILP has a serious b...
Cholwich Nattee, Sukree Sinthupinyo, Masayuki Numa...
AIIA
2005
Springer
14 years 1 months ago
Handling Continuous-Valued Attributes in Incremental First-Order Rules Learning
Machine Learning systems are often distinguished according to the kind of representation they use, which can be either propositional or first-order logic. The framework working wi...
Teresa Maria Altomare Basile, Floriana Esposito, N...
ICML
2006
IEEE
14 years 8 months ago
Bayesian learning of measurement and structural models
We present a Bayesian search algorithm for learning the structure of latent variable models of continuous variables. We stress the importance of applying search operators designed...
Ricardo Silva, Richard Scheines
IS
2010
13 years 6 months ago
Identifying user strategies in exploratory learning with evolving task modelling
Abstract—In this paper we present work on adaptive identification of learners’ strategies, gradually developing a higher level of adaptation based on evolving models of mathem...
Mihaela Cocea, George D. Magoulas
UAI
1998
13 years 9 months ago
A Multivariate Discretization Method for Learning Bayesian Networks from Mixed Data
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...
Stefano Monti, Gregory F. Cooper