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Cost-sensitive boosting for classification of imbalanced data
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.
Abstract
No abstract. This is not a gap in this database — OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
The record
- Venue
- Pattern Recognition
- Topic
- Imbalanced Data Classification Techniques
- Field
- Computer Science
- Canadian institutions
- Pattern Discovery Technologies (Canada)University of Waterloo
- Funders
- —
- Keywords
- Boosting (machine learning)TackingAdaBoostMachine learningArtificial intelligenceWeightingComputer scienceClassifier (UML)Statistical classificationData mining
- Has abstract in OpenAlex
- no