A Model Fusion Based Framework For Imbalanced Classification Problem with Noisy Dataset

A Model Fusion Based Framework For Imbalanced Classification Problem with Noisy Dataset

abstract: Data imbalance and data noise often coexist in real world datasets. Data imbalance affects the learning classifier by degrading the recognition power of the classifier on the minority class, while data noise affects the learning classifier by providing inaccurate information and thus misle...

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Bibliographic Details
Other Authors: He, Miao (Author)
Format: Doctoral Thesis
Language:English
Published: 2014
Subjects:
Industrial engineering
Information science
Gaussian mixture model
Imbalanced classification
K nearest Gaussian
Particle swarm optimization
Support vector machine
Online Access:http://hdl.handle.net/2286/R.I.26834

Internet

http://hdl.handle.net/2286/R.I.26834

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