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» Classification with Belief Decision Trees
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CSDA
2008
126views more  CSDA 2008»
13 years 9 months ago
A new genetic algorithm in proteomics: Feature selection for SELDI-TOF data
Mass spectrometry from clinical specimens is used in order to identify biomarkers in a diagnosis. Thus, a reliable method for both feature selection and classification is required...
Christelle Reynès, Robert Sabatier, Nicolas...
CORR
2010
Springer
106views Education» more  CORR 2010»
13 years 9 months ago
Further Exploration of the Dendritic Cell Algorithm: Antigen Multiplier and Time Windows
Abstract. As an immune-inspired algorithm, the Dendritic Cell Algorithm (DCA), produces promising performance in the field of anomaly detection. This paper presents the application...
Feng Gu, Julie Greensmith, Uwe Aickelin
BMCBI
2006
137views more  BMCBI 2006»
13 years 9 months ago
A classification-based framework for predicting and analyzing gene regulatory response
Background: We have recently introduced a predictive framework for studying gene transcriptional regulation in simpler organisms using a novel supervised learning algorithm called...
Anshul Kundaje, Manuel Middendorf, Mihir Shah, Chr...
CVPR
2006
IEEE
14 years 11 months ago
Supervised Learning of Edges and Object Boundaries
Edge detection is one of the most studied problems in computer vision, yet it remains a very challenging task. It is difficult since often the decision for an edge cannot be made ...
Piotr Dollár, Zhuowen Tu, Serge Belongie
IFIP12
2008
13 years 10 months ago
P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unse...
Frederic T. Stahl, Max A. Bramer, Mo Adda