資源描述：
《prml筆記-notes on pattern recognition and machine learning》由會員上傳分享，免費(fèi)在線閱讀，更多相關(guān)內(nèi)容在學(xué)術(shù)論文-天天文庫。
1、PRML筆記NotesonPatternRecognitionandMachineLearning(Bishop)Version1.0①JianXiao目錄Checklist.....................................................................................................2Chapter1Introduction................................................................................4Ch
2、apter2ProbabilityDistribution............................................................10..................................................14Chapter3LinearModelsforRegression..............................................19Chapter4LinearModelsforClassificationChapter5NeuralNetworks.........
3、.............................................................26Chapter6Kernelmethods........................................................................33Chapter7SparseKernelMachine............................................................39Chapter8GraphicalModels......................
4、...............................................47Chapter9MixtureModelsandEM..........................................................53Chapter10ApproximateInference...........................................................58Chapter11SamplingMethod............................................
5、.......................63Chapter12ContinuousLatentVariables..................................................68Chapter13SequentialData......................................................................72Chapter14CombiningModels..............................................................
6、...74①iamxiaojian@gmail.comChecklistFrequentist-Bayesian對峙構(gòu)成的主要內(nèi)容Frequentist版本Bayesian版本解模型所用的方法LinearbasisfunctionBayesianlinearbasisfunction前者和后者皆有closed-formregressionregressionsolutionLogisticregressionBayesianlogitsticregression前者牛頓迭代(IRLS)，后者LaplaceapproximationNeuralnetwork(forBayesia
7、nNeuralnetwork(for前者gradientdecent，后者regression,classification)regression,classification)LaplaceapproximationSVM(forregression,RVM(forregression,前者解二次規(guī)劃，后者迭代、classification)classification)LaplaceapproximationGaussianmixturemodelBayesianGaussianmixt
