4.5k citations · 5.6k across the 19 of their papers we have counts for
3 papers · 1 filter
Models and Selection Criteria for Regression and Classification
David Heckerman, Christopher Meek
When performing regression or classification, we are interested in the conditional probability distribution for an outcome or class variable Y given a set of explanatoryor input va…
Staged Mixture Modelling and Boosting
Christopher Meek, Bo Thiesson, David Heckerman
In this paper, we introduce and evaluate a data-driven staged mixture modeling technique for building density, regression, and classification models. Our basic approach is to seque…
Large-Sample Learning of Bayesian Networks is NP-Hard
David Maxwell Chickering, Christopher Meek, David Heckerman
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a s…