adaptive_adaboosting
所属分类:人工智能/神经网络/深度学习
开发工具:matlab
文件大小:6KB
下载次数:174
上传日期:2009-03-26 23:12:38
上 传 者:
pierre0219
说明: AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yoav Freund and Robert Schapire. In this project there two main files
文件列表:
adaptive_adaboosting (0, 2009-03-26)
adaptive_adaboosting\adaboost (0, 2009-03-26)
adaptive_adaboosting\adaboost\ADABOOST_te.m (2916, 2008-09-03)
adaptive_adaboosting\adaboost\ADABOOST_tr.m (4452, 2008-09-03)
adaptive_adaboosting\adaboost\demo.m (1849, 2008-09-03)
adaptive_adaboosting\adaboost\likelihood2class.m (812, 2008-09-03)
adaptive_adaboosting\adaboost\threshold_te.m (1467, 2008-09-03)
adaptive_adaboosting\adaboost\threshold_tr.m (2222, 2008-09-03)
README
--------
Directory contains the following files.
1. ADABOOST_te.m
2. ADABOOST_tr.m
3. demo.m
4. likelihood2class.m
5. threshold_te.m
6. threshold_tr.m
The aim of the project is to provide a source of the
meta-learning algorithm known as AdaBoost to improve
the performance of the user-defined classifiers.
To make use of adaboost, first two functions must be
run with the appropriate parameters. The explanation
of each source file is available with "help" command.
To see how they work, run demo.m as
>> demo
First three lines in demo.m specifies the training and
testing set size and the number of weak (threshold)
classifiers.
For bug reporting and for comments do not hesitate to
send e-mail to the author.
Cuneyt Mertayak
email: cuneyt.mertayak@gmail.com
version: 1.0
date: 03/09/2008
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