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MCS
2000
Springer
13 years 11 months ago
Analysis of a Fusion Method for Combining Marginal Classifiers
The use of multiple features by a classifier often leads to a reduced probability of error, but the design of an optimal Bayesian classifier for multiple features is dependent on t...
Mark D. Happel, Peter Bock
ICANNGA
2007
Springer
161views Algorithms» more  ICANNGA 2007»
13 years 11 months ago
Evolutionary Induction of Decision Trees for Misclassification Cost Minimization
Abstract. In the paper, a new method of decision tree learning for costsensitive classification is presented. In contrast to the traditional greedy top-down inducer in the proposed...
Marek Kretowski, Marek Grzes
BMCBI
2006
72views more  BMCBI 2006»
13 years 8 months ago
Selecting effective siRNA sequences by using radial basis function network and decision tree learning
Background: Although short interfering RNA (siRNA) has been widely used for studying gene functions in mammalian cells, its gene silencing efficacy varies markedly and there are o...
Shigeru Takasaki, Yoshihiro Kawamura, Akihiko Kona...
ICML
2009
IEEE
14 years 2 months 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
IGARSS
2010
13 years 2 months 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