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» A supervised learning approach for imbalanced data sets
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CORR
2010
Springer
73views Education» more  CORR 2010»
13 years 7 months ago
Exponential Family Hybrid Semi-Supervised Learning
We present an approach to semi-supervised learning based on an exponential family characterization. Our approach generalizes previous work on coupled priors for hybrid generative/...
Arvind Agarwal, Hal Daumé III
RSCTC
2010
Springer
142views Fuzzy Logic» more  RSCTC 2010»
13 years 5 months ago
Learning from Imbalanced Data in Presence of Noisy and Borderline Examples
In this paper we studied re-sampling methods for learning classifiers from imbalanced data. We carried out a series of experiments on artificial data sets to explore the impact of ...
Krystyna Napierala, Jerzy Stefanowski, Szymon Wilk
JMLR
2006
112views more  JMLR 2006»
13 years 7 months ago
Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting
We develop kernels for measuring the similarity between relational instances using background knowledge expressed in first-order logic. The method allows us to bridge the gap betw...
Andrea Passerini, Paolo Frasconi, Luc De Raedt
CORR
2006
Springer
127views Education» more  CORR 2006»
13 years 7 months ago
Semi-Supervised Learning -- A Statistical Physics Approach
We present a novel approach to semisupervised learning which is based on statistical physics. Most of the former work in the field of semi-supervised learning classifies the point...
Gad Getz, Noam Shental, Eytan Domany
FUIN
2011
358views Cryptology» more  FUIN 2011»
12 years 11 months ago
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopa...