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» A supervised learning approach for imbalanced data sets
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FLAIRS
2007
14 years 15 days ago
Enhancing the Performance of Semi-Supervised Classification Algorithms with Bridging
Traditional supervised classification algorithms require a large number of labelled examples to perform accurately. Semi-supervised classification algorithms attempt to overcome t...
Jason Chan, Josiah Poon, Irena Koprinska
ICAC
2005
IEEE
14 years 3 months ago
PICCIL: Interactive Learning to Support Log File Categorization
Motivated by the real-world application of categorizing system log messages into defined situation categories, this paper describes an interactive text categorization method, PICC...
David Loewenstern, Sheng Ma, Abdi Salahshour
MIR
2003
ACM
178views Multimedia» more  MIR 2003»
14 years 3 months ago
A bootstrapping approach to annotating large image collection
Huge amount of manual efforts are required to annotate large image/video archives with text annotations. Several recent works attempted to automate this task by employing supervis...
HuaMin Feng, Tat-Seng Chua
ICIP
2008
IEEE
14 years 12 months ago
Supervised image segmentation via ground truth decomposition
This paper proposes a data driven image segmentation algorithm, based on decomposing the target output (ground truth). Classical pixel labeling methods utilize machine learning al...
Ilya Levner, Russell Greiner, Hong Zhang
DATAMINE
2010
161views more  DATAMINE 2010»
13 years 7 months ago
Predicting labels for dyadic data
: In dyadic prediction, the input consists of a pair of items (a dyad), and the goal is to predict the value of an observation related to the dyad. Special cases of dyadic predicti...
Aditya Krishna Menon, Charles Elkan