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ICPR
2002
IEEE
14 years 6 months ago
Prototype Selection for Finding Efficient Representations of Dissimilarity Data
The nearest neighbor (NN) rule is a simple and intuitive method for solving classification problems. Originally, it uses distances to the complete training set. It performs well, ...
Elzbieta Pekalska, Robert P. W. Duin
PR
2006
102views more  PR 2006»
13 years 5 months ago
Prototype selection for dissimilarity-based classifiers
A conventional way to discriminate between objects represented by dissimilarities is the nearest neighbor method. A more efficient and sometimes a more accurate solution is offere...
Elzbieta Pekalska, Robert P. W. Duin, Pavel Pacl&i...
CVPR
2008
IEEE
14 years 7 months ago
Transfer learning for image classification with sparse prototype representations
To learn a new visual category from few examples, prior knowledge from unlabeled data as well as previous related categories may be useful. We develop a new method for transfer le...
Ariadna Quattoni, Michael Collins, Trevor Darrell
KDD
2000
ACM
142views Data Mining» more  KDD 2000»
13 years 9 months ago
Automating exploratory data analysis for efficient data mining
Having access to large data sets for the purpose of predictive data mining does not guarantee good models, even when the size of the training data is virtually unlimited. Instead,...
Jonathan D. Becher, Pavel Berkhin, Edmund Freeman
BMCBI
2008
208views more  BMCBI 2008»
13 years 5 months ago
GraphFind: enhancing graph searching by low support data mining techniques
Background: Biomedical and chemical databases are large and rapidly growing in size. Graphs naturally model such kinds of data. To fully exploit the wealth of information in these...
Alfredo Ferro, Rosalba Giugno, Misael Mongiov&igra...