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AIME
1997
Springer
15 years 8 months ago
Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods
We used Machine Learning (ML) methods to learn the best decision rules to distinguish normal brain aging from the earliest stages of dementia using subsamples of 198 normal and 244...
William Rodman Shankle, Subramani Mani, Michael J....
BMCBI
2010
143views more  BMCBI 2010»
15 years 4 months ago
Learning gene regulatory networks from only positive and unlabeled data
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Luigi Cerulo, Charles Elkan, Michele Ceccarelli
CVPR
2004
IEEE
16 years 6 months ago
Learning a Restricted Bayesian Network for Object Detection
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...
Henry Schneiderman
CVIU
2007
137views more  CVIU 2007»
15 years 4 months ago
Visual learning of texture descriptors for facial expression recognition in thermal imagery
Facial expression recognition is an active research area that finds a potential application in human emotion analysis. This work presents an illumination independent approach for...
Benjamín Hernández, Gustavo Olague, ...
TJS
2010
182views more  TJS 2010»
15 years 2 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari