文件名称:adaboost_for_matlab
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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
1. ADABOOST_tr.m
2. ADABOOST_te.m
to traing and test a user-coded learning (classification) algorithm with AdaBoost. A demo file (demo.m) is provided that demonstrates how these two files can be used with a classifier (basic threshold classifier) for two class classification problem.-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 1. ADABOOST_tr.m 2. ADABOOST_te.m to traing and test a user-coded learning (classification) algorithm with AdaBoost. A demo file (demo.m) is provided that demonstrates how these two files can be used with a classifier (basic threshold classifier) for two class classification problem.
1. ADABOOST_tr.m
2. ADABOOST_te.m
to traing and test a user-coded learning (classification) algorithm with AdaBoost. A demo file (demo.m) is provided that demonstrates how these two files can be used with a classifier (basic threshold classifier) for two class classification problem.-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 1. ADABOOST_tr.m 2. ADABOOST_te.m to traing and test a user-coded learning (classification) algorithm with AdaBoost. A demo file (demo.m) is provided that demonstrates how these two files can be used with a classifier (basic threshold classifier) for two class classification problem.
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下载文件列表
adaboost for matlab
...................\adaboost
...................\........\ADABOOST_te.m
...................\........\ADABOOST_tr.m
...................\........\demo.m
...................\........\likelihood2class.m
...................\........\README.txt
...................\........\threshold_te.m
...................\........\threshold_tr.m
...................\adaboost
...................\........\ADABOOST_te.m
...................\........\ADABOOST_tr.m
...................\........\demo.m
...................\........\likelihood2class.m
...................\........\README.txt
...................\........\threshold_te.m
...................\........\threshold_tr.m