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» On Semi-Supervised Classification
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ADBIS
2007
Springer
143views Database» more  ADBIS 2007»
14 years 1 months ago
Aggregating Multiple Instances in Relational Database Using Semi-Supervised Genetic Algorithm-based Clustering Technique
In solving the classification problem in relational data mining, traditional methods, for example, the C4.5 and its variants, usually require data transformations from datasets sto...
Rayner Alfred, Dimitar Kazakov
IJCAI
2003
13 years 9 months ago
Semi-Supervised Learning with Explicit Misclassification Modeling
This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This a...
Massih-Reza Amini, Patrick Gallinari
ICPR
2006
IEEE
14 years 8 months ago
A New Data Selection Principle for Semi-Supervised Incremental Learning
Current semi-supervised incremental learning approaches select unlabeled examples with predicted high confidence for model re-training. We show that for many applications this dat...
Alexander I. Rudnicky, Rong Zhang
ADMA
2009
Springer
246views Data Mining» more  ADMA 2009»
14 years 2 months ago
Semi Supervised Image Spam Hunter: A Regularized Discriminant EM Approach
Image spam is a new trend in the family of email spams. The new image spams employ a variety of image processing technologies to create random noises. In this paper, we propose a s...
Yan Gao, Ming Yang, Alok N. Choudhary
JMLR
2008
123views more  JMLR 2008»
13 years 7 months ago
Optimization Techniques for Semi-Supervised Support Vector Machines
Due to its wide applicability, the problem of semi-supervised classification is attracting increasing attention in machine learning. Semi-Supervised Support Vector Machines (S3VMs...
Olivier Chapelle, Vikas Sindhwani, S. Sathiya Keer...