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» A supervised learning approach for imbalanced data sets
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JMLR
2012
13 years 8 months ago
Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets
We propose a new method for comparing learning algorithms on multiple tasks which is based on a novel non-parametric test that we call the Poisson binomial test. The key aspect of...
Alexandre Lacoste, François Laviolette, Mar...
IFIP12
2008
15 years 7 months ago
A Study with Class Imbalance and Random Sampling for a Decision Tree Learning System
Sampling methods are a direct approach to tackle the problem of class imbalance. These methods sample a data set in order to alter the class distributions. Usually these methods ar...
Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Mar...
161
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IADIS
2003
15 years 7 months ago
Knowledge Discovery Process Supporting Organizational Learning
This paper stresses the contribution of the process of knowledge discovery in databases for the effective creation and sharing of organizational knowledge. The focus on the proces...
Isabel Ramos, Maribel Yasmina Santos
JMLR
2006
113views more  JMLR 2006»
15 years 6 months ago
Learning the Structure of Linear Latent Variable Models
We describe anytime search procedures that (1) find disjoint subsets of recorded variables for which the members of each subset are d-separated by a single common unrecorded cause...
Ricardo Silva, Richard Scheines, Clark Glymour, Pe...
ICML
2009
IEEE
16 years 1 months ago
Fast evolutionary maximum margin clustering
The maximum margin clustering approach is a recently proposed extension of the concept of support vector machines to the clustering problem. Briefly stated, it aims at finding a...
Fabian Gieseke, Tapio Pahikkala, Oliver Kramer