adaboost

Version 1.1.0.0 (11.9 MB) by niranjantdesai
The Adaboost method for creating a strong binary classifier from a series of weak classifiers
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Updated 26 May 2018

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adaboost

The Adaboost method for creating a strong binary classifier from a series of weak classifiers is implemented in this project. We use decision stumps as our weak classifiers. Classification results are shown for some synthetic datasets and the MNIST dataset containing images of digits.

Usage

Refer question 1 from the file hw4.pdf. All subparts have been implemented. Run /code/myMainScript.m to generate the results for the subparts sequentially. The function descriptions are provided in the respective files.

Cite As

niranjantdesai (2026). adaboost (https://www.mathworks.com/matlabcentral/fileexchange/57176-adaboost), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2015a
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes
1.1.0.0

Added train-images.idx3-ubyte
1.0.0.0