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» A Comparison of Approaches for Learning Probability Trees
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IGARSS
2010
13 years 19 days ago
Calibrating probabilities for hyperspectral classification of rock types
This paper investigates the performance of machine learning methods for classifying rock types from hyperspectral data. The main objective is to test the impact on classification ...
Sildomar T. Monteiro, Richard J. Murphy
UAI
2001
13 years 7 months ago
Markov Chain Monte Carlo using Tree-Based Priors on Model Structure
We present a general framework for defining priors on model structure and sampling from the posterior using the Metropolis-Hastings algorithm. The key ideas are that structure pri...
Nicos Angelopoulos, James Cussens
MICCAI
2005
Springer
14 years 6 months ago
MRI Tissue Classification with Neighborhood Statistics: A Nonparametric, Entropy-Minimizing Approach
We introduce a novel approach for magnetic resonance image (MRI) brain tissue classification by learning image neighborhood statistics from noisy input data using nonparametric den...
Tolga Tasdizen, Suyash P. Awate, Ross T. Whitaker,...
NIPS
1990
13 years 7 months ago
Bumptrees for Efficient Function, Constraint and Classification Learning
A new class of data structures called "bumptrees" is described. These structures are useful for efficiently implementing a number of neural network related operations. A...
Stephen M. Omohundro
ICML
2009
IEEE
14 years 17 days ago
Decision tree and instance-based learning for label ranking
The label ranking problem consists of learning a model that maps instances to total orders over a finite set of predefined labels. This paper introduces new methods for label ra...
Weiwei Cheng, Jens C. Huhn, Eyke Hüllermeier