This repository is the code for our BU EC503 Project
Authors: Tayler Pauls, Shen Shen and Alexander Oleinik
- adaboost part for all the plotting and result data relative to adaboost model analyse, run the ada.m in Matlab to get the result. 'BostonListing.mat' file is required for runing the code, It could be downloaded from Assignment repository or download from http://data.insideairbnb.com/united-states/ma/boston/2017-10-06/data/listings.csv.gz.
- gradient boosting for all the plotting and result data relative to adaboost model analyse, run the gradient_boosting to get the result. The code rely on sklearn library.
- the noise comparison code is contained in the comparison folder in files boston.py, mnist.py and regress.py the code is written in python3 and relies on the sklearn library. The boston housing data is also used for the demonstration of the multi-class classification capability of AdaBoost and Gradient Boost