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On the Combination of Logistic Regression and Local Probability Estimates
- Source :
- African Journal of Information & Communication Technology; Vol 5 No 2 (2009)
- Publication Year :
- 2009
- Publisher :
- University of Technology, Sydney (UTS), 2009.
-
Abstract
- In this paper we give a survey of the combination of classifiers. We briefly describe basic principles of machine learning and the problem of classifier construction and review several approaches to generate different classifiers as well as established methods to combine different classifiers. Then, we introduce our novel approach to assess the appropriateness of different classifiers based on their characteristics for each test point individually
- Subjects :
- Probabilistic classification
business.industry
Computer science
logistic regression
classifier characteristics
Pattern recognition
Linear classifier
Quadratic classifier
Machine learning
computer.software_genre
Logistic regression
Random subspace method
Naive Bayes classifier
machine learning
ComputingMethodologies_PATTERNRECOGNITION
k-nearest neighbor classification
classifier combination
General Materials Science
ensemble classification
Artificial intelligence
business
computer
Classifier (UML)
Cascading classifiers
Subjects
Details
- ISSN :
- 14492679
- Volume :
- 5
- Database :
- OpenAIRE
- Journal :
- African Journal of Information & Communication Technology
- Accession number :
- edsair.doi.dedup.....d541b5af438726670544ce9322efdcaf
- Full Text :
- https://doi.org/10.5130/ajict.v5i2.1152