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» Graph model selection using maximum likelihood
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ISBI
2004
IEEE
14 years 8 months ago
Likelihood Function Analysis for Segmentation of Mammographic Masses for Various Margin Groups
The purpose of this work was to develop an automatic boundary detection method for mammographic masses and to observe the method's performance on different four of the five m...
Lisa Kinnard, Shih-Chung Ben Lo, Erini Makariou, T...
ISNN
2009
Springer
14 years 2 months ago
A New Instance-Based Label Ranking Approach Using the Mallows Model
In this paper, we introduce a new instance-based approach to the label ranking problem. This approach is based on a probability model on rankings which is known as the Mallows mode...
Weiwei Cheng, Eyke Hüllermeier
NIPS
2007
13 years 9 months ago
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashi...
ICPR
2002
IEEE
14 years 8 months ago
Two-Hand Gesture Recognition using Coupled Switching Linear Model
We present a method coupling multiple switching linear models. The coupled switching linear model is an interactive process of two switching linear models. Coupling is given throu...
Mun Ho Jeong, Yoshinori Kuno, Nobutaka Shimada, Yo...
APAQS
2000
IEEE
13 years 12 months ago
Software Quality Prediction Using Mixture Models with EM Algorithm
The use of the statistical technique of mixture model analysis as a tool for early prediction of fault-prone program modules is investigated. The Expectation-Maximum likelihood (E...
Ping Guo, Michael R. Lyu