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Classic AdaBoost Classifier

version 1.5.0.0 (4.07 KB) by Dirk-Jan Kroon
Weak threshold classifier boosted to strong Classifier with Adaboost

19.4K Downloads

Updated 20 Jan 2012

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This a classic AdaBoost implementation, in one single file with easy understandable code.

The function consist of two parts a simple weak classifier and a boosting part:
The weak classifier tries to find the best threshold in one of the data dimensions to separate the data into two classes -1 and 1
The boosting part calls the classifier iteratively, after every classification step it changes the weights of miss-classified examples. This creates a cascade of "weak classifiers" which behaves like a "strong classifier"
.
Training mode:
[estimateclass,model]=adaboost('train',datafeatures,dataclass,itt)
Apply mode:
estimateclass=adaboost('apply',datafeatures,model)

inputs/outputs:
datafeatures : An Array with size number_samples x number_features
dataclass : An array with the class off all examples, the class
can be -1 or 1
itt : The number of training iterations
model : A struct with the cascade of weak-classifiers
estimateclass : The by the adaboost model classified data

.
Please leave a comment, if you like the code, find a bug or have a suggestion.

Cite As

Dirk-Jan Kroon (2021). Classic AdaBoost Classifier (https://www.mathworks.com/matlabcentral/fileexchange/27813-classic-adaboost-classifier), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2010a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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