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» Measuring the Complexity of Classification Problems
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VLSISP
2002
124views more  VLSISP 2002»
13 years 7 months ago
Agglomerative Learning Algorithms for General Fuzzy Min-Max Neural Network
In this paper two agglomerative learning algorithms based on new similarity measures defined for hyperbox fuzzy sets are proposed. They are presented in a context of clustering and...
Bogdan Gabrys
ICCV
2009
IEEE
13 years 5 months ago
Learning image similarity from Flickr groups using Stochastic Intersection Kernel MAchines
Measuring image similarity is a central topic in computer vision. In this paper, we learn similarity from Flickr groups and use it to organize photos. Two images are similar if th...
Gang Wang, Derek Hoiem, David A. Forsyth
JMLR
2010
121views more  JMLR 2010»
13 years 2 months ago
A comparison of AUC estimators in small-sample studies
Reliable estimation of the classification performance of learned predictive models is difficult, when working in the small sample setting. When dealing with biological data it is ...
Antti Airola, Tapio Pahikkala, Willem Waegeman, Be...
PRL
2000
182views more  PRL 2000»
13 years 7 months ago
Bayesian MLP neural networks for image analysis
We demonstrate the advantages of using Bayesian multi layer perceptron (MLP) neural networks for image analysis. The Bayesian approach provides consistent way to do inference by c...
Aki Vehtari, Jouko Lampinen
JMMA
2002
90views more  JMMA 2002»
13 years 7 months ago
Implicit Convex Polygons
Convex polygons in the plane can be defined explicitly as an ordered list of vertices, or given implicitly, for example by a list of linear constraints. The latter representation h...
Francisco Gómez, Ferran Hurtado, Suneeta Ra...