代码搜索：meta-learning

找到约 26 项符合「meta-learning」的源代码

代码结果 26
热门代码： main.c GPIO I2C SPI UART timer interrupt ADC PWM LED
www.eeworm.com/read/418755/10928192

txt readme.txt

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
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www.eeworm.com/read/467949/6997143

txt readme.txt

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
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www.eeworm.com/read/439518/7706976

txt readme.txt

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
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www.eeworm.com/read/439513/7707454

txt readme.txt

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
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www.eeworm.com/read/489934/6463612

txt readme.txt

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
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www.eeworm.com/read/290481/8481434

pdf tracking context changes through meta-learning(4).pdf

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www.eeworm.com/read/367675/2839010

txt 318.txt

发信人: daniel (飞翔鸟), 信区: DataMining 标 题: Re: 什么是meta-learning?应如何翻译? 发信站: 南京大学小百合站 (Wed Apr 10 18:48:28 2002), 站内信件 Note that meta-learning is not a same concept to combining classfiers, or mor
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www.eeworm.com/read/252976/12252067

readme

NOTE: this file was last updated with r35 check updates at: http://code.google.com/p/icsiboost Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form a s
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www.eeworm.com/read/418755/10928183

m adaboost_tr.m

function adaboost_model = ADABOOST_tr(tr_func_handle, te_func_handle, train_set, labels, no_of_hypothesis) % % ADABOOST TRAINING: A META-LEARNING ALGORITHM % adaboost_model = ADABOOST_tr(tr_func_hand
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www.eeworm.com/read/467949/6997138

m adaboost_tr.m

function adaboost_model = ADABOOST_tr(tr_func_handle, te_func_handle, train_set, labels, no_of_hypothesis) % % ADABOOST TRAINING: A META-LEARNING ALGORITHM % adaboost_model = ADABOOST_tr(tr_func_hand
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