Error Correcting Output Codes (ECOC) Classifier
"Error Correcting Output Codes (ECOC) for multi-class classification".
Different code matrices i.e. one vs.one, one vs.All, dense random and sparse random implemented. You have also opportunity to cheese between MLP neural network and Support Vector Machine Classifiers.
- Open Matlab, change directory and Run "Demo.m"
- In demo, I use Segment dataset just to show how the code works. You should have your dataset prepared in that format.
- To read more, go to folder "papers".
Citations:
- Nima Hatami: Thinned-ECOC ensemble based on sequential code shrinking. Expert Syst. Appl. 39(1): 936-947 (2012)
- Giuliano Armano, Camelia Chira, Nima Hatami: Ensemble of Binary Learners for Reliable Text Categorization with a Reject Option. HAIS (1) 2012: 137-146
- Giuliano Armano, Camelia Chira, Nima Hatami: Error-Correcting Output Codes for Multi-Label Text Categorization. IIR 2012: 26-37
Cite As
Nima Hatami (2024). Error Correcting Output Codes (ECOC) Classifier (https://www.mathworks.com/matlabcentral/fileexchange/47405-error-correcting-output-codes-ecoc-classifier), MATLAB Central File Exchange. Retrieved .
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- AI, Data Science, and Statistics > Statistics and Machine Learning Toolbox > Classification > Classification Ensembles >
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