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AAAI
1996
15 years 2 months ago
Bagging, Boosting, and C4.5
Breiman's bagging and Freund and Schapire's boosting are recent methods for improving the predictive power of classi er learning systems. Both form a set of classi ers t...
J. Ross Quinlan
CVPR
2008
IEEE
16 years 3 months ago
A hierarchical and contextual model for aerial image understanding
In this paper we present a novel method for parsing aerial images with a hierarchical and contextual model learned in a statistical framework. We learn hierarchies at the scene an...
Jake Porway, Kristy Wang, Benjamin Yao, Song Chun ...
ICML
2005
IEEE
16 years 2 months ago
Bayesian hierarchical clustering
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
Katherine A. Heller, Zoubin Ghahramani
ICML
1997
IEEE
16 years 2 months ago
An adaptation of Relief for attribute estimation in regression
Heuristic measures for estimating the quality of attributes mostly assume the independence of attributes so in domains with strong dependencies between attributes their performanc...
Marko Robnik-Sikonja, Igor Kononenko
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
16 years 1 months ago
Exploiting unlabeled data in ensemble methods
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
Kristin P. Bennett, Ayhan Demiriz, Richard Maclin