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CSDA
2007
202views more  CSDA 2007»
15 years 4 months ago
Bayesian estimation of the Gaussian mixture GARCH model
In this paper, we perform Bayesian inference and prediction for a GARCH model where the innovations are assumed to follow a mixture of two Gaussian distributions. This GARCH model...
María Concepción Ausín, Pedro...
ICML
2005
IEEE
16 years 5 months ago
Predicting good probabilities with supervised learning
We examine the relationship between the predictions made by different learning algorithms and true posterior probabilities. We show that maximum margin methods such as boosted tre...
Alexandru Niculescu-Mizil, Rich Caruana
DIS
1998
Springer
15 years 9 months ago
Learning with Globally Predictive Tests
We introduce a new bias for rule learning systems. The bias only allows a rule learner to create a rule that predicts class membership if each test of the rule in isolation is pred...
Michael J. Pazzani
ICMLA
2008
15 years 6 months ago
Predicting Algorithm Accuracy with a Small Set of Effective Meta-Features
We revisit 26 meta-features typically used in the context of meta-learning for model selection. Using visual analysis and computational complexity considerations, we find 4 meta-f...
Jun Won Lee, Christophe G. Giraud-Carrier
235
Voted
GIS
2008
ACM
16 years 5 months ago
Pedestrian flow prediction in extensive road networks using biased observational data
In this paper, we discuss an application of spatial data mining to predict pedestrian flow in extensive road networks using a large biased sample. Existing out-of-the-box techniqu...
Michael May, Simon Scheider, Roberto Rösler, ...