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ASUNAM
2010
IEEE
13 years 11 months ago
Semi-Supervised Classification of Network Data Using Very Few Labels
The goal of semi-supervised learning (SSL) methods is to reduce the amount of labeled training data required by learning from both labeled and unlabeled instances. Macskassy and Pr...
Frank Lin, William W. Cohen
GCB
2003
Springer
164views Biometrics» more  GCB 2003»
14 years 2 months ago
Integrative machine learning approach for multi-class SCOP protein fold classification
: Classification and prediction of protein structure has been a central research theme in structural bioinformatics. Due to the imbalanced distribution of proteins over multi SCOP ...
Aik Choon Tan, David Gilbert, Yves Deville
AAAI
2008
14 years 10 hour ago
Multi-View Local Learning
The idea of local learning, i.e., classifying a particular example based on its neighbors, has been successfully applied to many semi-supervised and clustering problems recently. ...
Dan Zhang, Fei Wang, Changshui Zhang, Tao Li
ICML
2000
IEEE
14 years 10 months ago
Discovering Test Set Regularities in Relational Domains
Machine learning typically involves discovering regularities in a training set, then applying these learned regularities to classify objects in a test set. In this paper we presen...
Seán Slattery, Tom M. Mitchell
ICML
2007
IEEE
14 years 10 months ago
Experimental perspectives on learning from imbalanced data
We present a comprehensive suite of experimentation on the subject of learning from imbalanced data. When classes are imbalanced, many learning algorithms can suffer from the pers...
Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napol...