Provide a unified conceptual and software framework encompassing machine learning, graphical models, and Bayesian statistics

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

• We are an exchange download platform that only provides communication channels. The downloaded content comes from the internet. Except for download issues, please Google on your own.
• The downloaded content is provided for members to upload. If it unintentionally infringes on your copyright, please contact us.
• Please use Winrar for decompression tools
• If download fail, Try it againg or Feedback to us.
• If downloaded content did not match the introduction, Feedback to us，Confirm and will be refund.
• Before downloading, you can inquire through the uploaded person information

Nothing．