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» Learning with Mixtures of Trees
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ML
2000
ACM
157views Machine Learning» more  ML 2000»
13 years 7 months ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins
GECCO
2009
Springer
101views Optimization» more  GECCO 2009»
14 years 2 months ago
Modeling UCS as a mixture of experts
We present a probabilistic formulation of UCS (a sUpervised Classifier System). UCS is shown to be a special case of mixture of experts where the experts are learned independentl...
Narayanan Unny Edakunni, Tim Kovacs, Gavin Brown, ...
VLSISP
1998
111views more  VLSISP 1998»
13 years 7 months ago
Quantitative Analysis of MR Brain Image Sequences by Adaptive Self-Organizing Finite Mixtures
This paper presents an adaptive structure self-organizing finite mixture network for quantification of magnetic resonance (MR) brain image sequences. We present justification fo...
Yue Wang, Tülay Adali, Chi-Ming Lau, Sun-Yuan...
ICML
2005
IEEE
14 years 8 months ago
Predicting probability distributions for surf height using an ensemble of mixture density networks
There is a range of potential applications of Machine Learning where it would be more useful to predict the probability distribution for a variable rather than simply the most lik...
Michael Carney, Padraig Cunningham, Jim Dowling, C...
ALT
2003
Springer
13 years 11 months ago
Efficient Learning of Ordered and Unordered Tree Patterns with Contractible Variables
Due to the rapid growth of tree structured data such as Web documents, efficient learning from tree structured data becomes more and more important. In order to represent structura...
Yusuke Suzuki, Takayoshi Shoudai, Satoshi Matsumot...