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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