Adaboost Matlab Toolbox Manual

Topics: Boosting, Decision tree, Tree Pages: 12 (3286 words) Published: October 12, 2012
GML AdaBoost Matlab Toolbox Manual
This manual describes the usage of GML AdaBoost matlab toolbox, and is organized as follows: in the first section will introduce you to the basic concept of the toolbox, then we give an example script that uses the toolbox, section 3 speaks about all available functions and classes and section 4 is Q and A. Introduction ...................................................................................................................................1 Implemented algorithms ...........................................................................................................2 Available weak learners ............................................................................................................2 CART......................................................................................................................................2 Additional functionalities..........................................................................................................3 Authors .......................................................................................................................................4 Library structure and usage.........................................................................................................4 Functions and Classes ...............................................................................................................4 function [Learners, Weights, {final_hyp}] = RealAdaBoost(WeakLrn, Data, Labels, Max_Iter, {OldW, OldLrn, final_hyp})...............................................................................4 function [Learners, Weights, {final_hyp}] = GentleAdaBoost(WeakLrn, Data, Labels, Max_Iter, {OldW, OldLrn}).................................................................................................5 function [Learners, Weights, {final_hyp}] = ModestAdaBoost(WeakLrn, Data, Labels, Max_Iter, {OldW, OldLrn}).................................................................................................5 function Result = Classify(Learners, Weights, Data).........................................................5 function code = TranslateToC (Learners, Weights, fid) ....................................................5 @tree_node_w : .....................................................................................................................6 @crossvalidation : .................................................................................................................6 Example scripts..............................................................................................................................7 Example_1 script .......................................................................................................................7 Comments on the script ........................................................................................................7 Example_2 script .......................................................................................................................7 Comments on the script ........................................................................................................9 Example_3 script .......................................................................................................................9 Comments on the script ......................................................................................................11 TrainAndSave script ...............................................................................................................11 Comments on the script ......................................................................................................11 Q and A: .......................................................................................................................................11 What version of Matlab should I have for the toolbox to work? ........................................11...
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