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» Strong Separation of Learning Classes
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ICMLA
2007
13 years 8 months ago
Estimating class probabilities in random forests
For both single probability estimation trees (PETs) and ensembles of such trees, commonly employed class probability estimates correct the observed relative class frequencies in e...
Henrik Boström
UAI
2004
13 years 8 months ago
Factored Latent Analysis for far-field Tracking Data
This paper uses Factored Latent Analysis (FLA) to learn a factorized, segmental representation for observations of tracked objects over time. Factored Latent Analysis is latent cl...
Chris Stauffer
UAIS
2008
88views more  UAIS 2008»
13 years 7 months ago
Utilizing Wiki-Systems in higher education classes: a chance for universal access?
Abstract Wikis are a website technology for mass collaborative authoring. Today, wikis are increasingly used for educational purposes. Basically, the most important asset of wikis ...
Martin Ebner, Michael D. Kickmeier-Rust, Andreas H...
ICPR
2002
IEEE
14 years 8 months ago
To Each According to its Need: Kernel Class Specific Classifiers
We present in this paper a new multi-class Bayes classifier that permits using separate feature vectors, chosen specifically for each class. This technique extends previous work o...
Barbara Caputo, Heinrich Niemann
COLT
2006
Springer
13 years 11 months ago
Discriminative Learning Can Succeed Where Generative Learning Fails
Generative algorithms for learning classifiers use training data to separately estimate a probability model for each class. New items are classified by comparing their probabiliti...
Philip M. Long, Rocco A. Servedio