文件名称:RVM2
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基于稀疏贝叶斯框架的机器学习算法，能有效用于回归和分类预测，具有较强的泛化性-Machine learning algorithm based on sparse Bayesian framework, can effectively be used for regression and classification forecast has good generalization
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下载文件列表
SB2_Release_200/licence.txt
SB2_Release_200/Readme.txt
SB2_Release_200/SB2_ControlSettings.m
SB2_Release_200/SB2_Diagnostic.m
SB2_Release_200/SB2_FormatTime.m
SB2_Release_200/SB2_FullStatistics.m
SB2_Release_200/SB2_Initialisation.m
SB2_Release_200/SB2_Likelihoods.m
SB2_Release_200/SB2_Manual.pdf
SB2_Release_200/SB2_ParameterSettings.m
SB2_Release_200/SB2_PosteriorMode.m
SB2_Release_200/SB2_PreProcessBasis.m
SB2_Release_200/SB2_Sigmoid.m
SB2_Release_200/SB2_UserOptions.m
SB2_Release_200/SparseBayes.m
SB2_Release_200/SparseBayesDemo.m
SB2_Release_200
SB2_Release_200/Readme.txt
SB2_Release_200/SB2_ControlSettings.m
SB2_Release_200/SB2_Diagnostic.m
SB2_Release_200/SB2_FormatTime.m
SB2_Release_200/SB2_FullStatistics.m
SB2_Release_200/SB2_Initialisation.m
SB2_Release_200/SB2_Likelihoods.m
SB2_Release_200/SB2_Manual.pdf
SB2_Release_200/SB2_ParameterSettings.m
SB2_Release_200/SB2_PosteriorMode.m
SB2_Release_200/SB2_PreProcessBasis.m
SB2_Release_200/SB2_Sigmoid.m
SB2_Release_200/SB2_UserOptions.m
SB2_Release_200/SparseBayes.m
SB2_Release_200/SparseBayesDemo.m
SB2_Release_200
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