文件名称:pmtk3-24October2010

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  • matlab例程
  • 资源属性:
  • [Matlab] [源码]
  • 上传时间:
  • 2012-11-26
  • 文件大小:
  • 4.21mb
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  • 0次
  • 提 供 者:
  • 汪*
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关于贝叶斯统计估计,图像模型,概率计算的程序包-Provide a unified conceptual and software fr a mework encompassing machine learning, graphical models, and Bayesian statistics
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下载文件列表

pmtk3

.....\config.txt

.....\data

.....\demos

.....\.....\bookDemos

.....\.....\.........\Bayesian_statistics_I

.....\.....\.........\.....................\bernoulliBetaSequentialUpdate.m

.....\.....\.........\.....................\betaBinomPostPredDemo.m

.....\.....\.........\.....................\bimodalDemo.m

.....\.....\.........\.....................\binomialBetaPosteriorDemo.m

.....\.....\.........\.....................\gaussInferParamsMean1d.m

.....\.....\.........\.....................\gaussSeqlUpdateMuSigma1D.m

.....\.....\.........\.....................\gaussSeqUpdateSigma1D.m

.....\.....\.........\.....................\healthyLevels.m

.....\.....\.........\.....................\NIXdemo2.m

.....\.....\.........\.....................\numbersGame.m

.....\.....\.........\.....................\sensorFusionUnknownPrec.m

.....\.....\.........\Bayesian_statistics_II

.....\.....\.........\......................\bayesTtestDemo.m

.....\.....\.........\......................\betaCredibleInt.m

.....\.....\.........\......................\betaHPD.m

.....\.....\.........\......................\cancerRatesEb.m

.....\.....\.........\......................\cancerRatesMh.m

.....\.....\.........\......................\coinsModelSelDemo.m

.....\.....\.........\......................\mixBetaDemo.m

.....\.....\.........\......................\newcombPlugin.m

.....\.....\.........\......................\postDensityIntervals.m

.....\.....\.........\......................\shrinkageDemoBaseball.m

.....\.....\.........\Bound_optimization_and_the_EM_algorithm

.....\.....\.........\.......................................\emLogLikelihoodMax.m

.....\.....\.........\.......................................\mixGaussOverRelaxedEmDemo.m

.....\.....\.........\Clustering

.....\.....\.........\..........\kmeansDemoFaithful.m

.....\.....\.........\..........\kmeansModelSel1d.m

.....\.....\.........\..........\kmeansModelSel2d.m

.....\.....\.........\..........\mixGaussDemoFaithful.m

.....\.....\.........\..........\mixGaussLikSurfaceDemo.m

.....\.....\.........\..........\mixGaussMLvsMAP.m

.....\.....\.........\..........\mixGaussSingularity.m

.....\.....\.........\..........\mixGaussVbDemoFaithful.m

.....\.....\.........\..........\mixStudentBankruptcyDemo.m

.....\.....\.........\..........\parzenWindowDemo.m

.....\.....\.........\..........\vqDemo.m

.....\.....\.........\Constrained_optimization

.....\.....\.........\........................\saddle.m

.....\.....\.........\Convex_analysis

.....\.....\.........\...............\conjugateFunction.m

.....\.....\.........\...............\jensensInequalityFigure.m

.....\.....\.........\...............\optLowerbound.m

.....\.....\.........\Decision_theory

.....\.....\.........\...............\hingeLossPlot.m

.....\.....\.........\...............\knnClassifyDemo.m

.....\.....\.........\...............\linregPolyVsRegDemo.m

.....\.....\.........\...............\lossFunctionFig.m

.....\.....\.........\...............\PRhand.m

.....\.....\.........\...............\riskFnGauss.m

.....\.....\.........\...............\ROChand.m

.....\.....\.........\Deep_Generative_Models

.....\.....\.........\......................\deepBelNetClassifyDemo.m

.....\.....\.........\......................\deepBelNetDemo.m

.....\.....\.........\......................\mnistSubset.mat

.....\.....\.........\......................\rbmClassifyDemo.m

.....\.....\.........\......................\rbmDenoiseDemo.m

.....\.....\.........\Directed_graphical_models_Bayes_nets

.....\.....\.........\....................................\errorCorrectingCodeDemo.m

.....\.....\.........\....................................\lungcancerGMdemo.m

.....\.....\.........\Discrete_optimization

.....\.....\.........\.....................\saDemoPeaks.m

.....\.....\.........\Discriminative_models_for_regression_and_classification

.....\.....\.........\.......................................................\bayesLinRegDemo2d.m

.....\.....\.........\.......................................................\leastSquaresProjection.m

.....\.....\.........\................

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