README --------Directory contains the following files.1. ADABOOST_te.m2. ADABOOST_tr.m3. demo.m4. likelihood2class.m5. threshold_te.m6. threshold_tr.mThe aim of the project is to provide a source of themeta-learning algorithm known as AdaBoost to improvethe performance of the user-defined classifiers.To make use of adaboost, first two functions must berun with the appropriate parameters. The explanationof each source file is available with "help" command.To see how they work, run demo.m as>> demoFirst three lines in demo.m specifies the training andtesting set size and the number of weak (threshold)classifiers.For bug reporting and for comments do not hesitate tosend e-mail to the author.Cuneyt Mertayakemail: cuneyt.mertayak@gmail.comversion: 1.0date: 03/09/2008