国家地理信息，用geoda文件可以打开，生成权重文件，或者进行空间计量分析

mybase绿色免安装版本，离线笔记中最好用的一个，推荐使用。
在线笔记推荐有道和为知笔记。
不过有些环境不能使用在线笔记，此时使用这个笔记最好不过了。
此版本为7.0（windows）

SCI翻译软件，还可以，用起来，对于英语不好的我，分享一下SCITranslate12.rar

本书介绍了一个使用sasEM6.1进行数据挖掘的案例，包括决策树、神经网络和逻辑回归。

灰度图像的二维Otsu自动阈值分割法matlab源程序,这个程序不错，还能计算时间和二维直方图

针对大小为2^n*2^n的图像进行重叠分块并重构，分块大小也是2的幂次.也可实现图像处理中的滑窗技术(slidingtechnique)

数据比较全面，从其他地方整理过来，可以下载试试，中国地面气候资料日值数据集（V3.0）"包含了中国824个基准、基本气象站本站气压、气温、降水量、蒸发量、相对湿度、风向风速、日照时数和0cm地温要素的日值数据。
2010年~2017年10月数据

本文通过Matlab软件对在静电场条件下的对导体内的电子注对运动规律进行了模拟仿真，完成的最终波形结果。

发现现在CSDN的下载资源的分数都太高了，我还是秉承低分共享原则，分下一个东西给大家吧

DaphneKoller关于ProbabilisticGraphicalModels的最权威大作，内容详实深入，是各大名校机器学习和人工智能专业相应课程的指定教材AdaptiveComputationandMachineLearningThomasdietterich,EditorChristopherBishop,DavidHeckerman,MichaelJordan,andMichaelKearns,AssociateEditorsBioinformatics:TheMachinelearningApproach,PierreBaldiandSorenBrunakReinforcementLearning:AnIntroduction,RichardS.SuttonandAndrewG.BartoGraphicalmodelsforMachineLearningandDigitalCommunication,BrendanJ.FreyLearningingraphicalModels,MichaelI.JordanCausation,Prediction,andSearch,2nded,PeterSpirtes,ClarkGlymour,andRichardScheinesPrinciplesofDataMining,DavidHand,HeikkiMannila,andPadhraicSmythBioinformatics:TheMachineLearningApproach,2nded,PierreBaldiandSorenBrunakLearningKernelclassifiers:TheoryandAlgorithms,RalfHerbrichLearningwithKernels:SupportVectorMachines,Regularization,Optimization,andBeyond,BernhardScholkopfandAlexanderJsmolaIntroductiontoMachineLearning,EthemAlpaydinGaussianProcessesforMachineLearning,CarlEdwardRasmussenandChristopherK.I.WilliamsSemi-SupervisedLearning,OlivierChapelle,BernhardScholkopf,andAlexanderZien,edsTheMinimumdescriptionLengthPrinciple,PeterDGrunwaldIntroductiontoStatisticalRelationalLearning,liseGetoorandBenTaskar,edsProbabilisticGraphicalModels:PrinciplesandTechniques,DaphneKollerandNirFriedmanProbabilisticGraphicalModelsPrinciplesandTechniquesDaphnekollerNirfriedmanThemitpressCambridge,MassachusettsLondon,England@2009MassachusettsInstituteofTechnologyAllrightsreserved.Nopartofthisbookmaybereproducedinanyformbyanyelectronicormechanicalmeans(includingphotocopying,recording,orinformationstorageandretrieval)withoutpermissioninwritingfromthepublisherForinformationaboutspecialquantitydiscounts,pleaseemailspecial_sales@mitpress.mit.eduThisbookwassetbytheauthorsinBlFX2EPrintedandboundintheunitedstatesofamericaLibraryofCongressCataloging-in-PublicationDataKoller,DaphneProbabilisticGraphicalModels:PrinciplesandTechniquesDaphneKollerandNirFriedmanpcm.-(Adaptivecomputationandmachinelearning)IncludesbibliographicalreferencesandindexisBn978-0-262-01319-2(hardcover:alk.paper1.Graphicalmodeling(Statistics)2.Bayesianstatisticaldecisiontheory--Graphicmethods.IKoller,Daphne.II.Friedman,NirQA279.5.K652010519.5’420285-dc222009008615109876543ToourfamiliesmyparentsDovandditzamyhusbanddanmydaughtersnatalieandmayaDKmyparentsNogaandGadmywifemychildrenroyandliorMEAsfarasthelawsofmathematicsrefertoreality,theyarenotcertain,asfarastheyarecertain,theydonotrefertorealityAlberteinstein1956Whenwetrytopickoutanythingbyitself,wefindthatitisboundfastbyathousandinvisiblecordsthatcannotbebroken,toeverythingintheuniverseJohnMuir,1869Theactualscienceoflogicisconversantatpresentonlywiththingseithercertain,impossible,orentirelydoubtful.Thereforethetruelogicforthisworldisthecalculusofprobabilities,whichtakesaccountofthemagnitudeoftheprobabilitywhichis,oroughttobe,inareasonableman'smindJamesClerkMaxwell,1850Thetheoryofprobabilitiesisatbottomnothingbutcommonsensereducedtocalculus;itenablesustoappreciatewithexactnessthatwhichaccuratemindsfeelwithasortofinstinctforwhichofttimestheyareunabletoaccount.PierreSimonLaplace,1819MisunderstandingofprobabilitymaybethegreatestofallimpedimentstoscientificliteracyStephenJayGouldContentsAcknowledgmentsListoffiguresListofalgorithmsListofboxesXXX1IntroductionL1Motivation11.2StructuredProbabilisticModels21.2.1ProbabilisticGraphicalModels31.2.2Representation,Inference,Learning51.3Overviewandroadmap61.3.1OverviewofChapters61.3.2Readersguide1.3.3ConnectiontoOtherDisciplines1.4Historicalnotes122Foundations2.1ProbabilityTheory2.1.1ProbabilityDistributions152.1.2BasicConceptsinProbability182.1.3RandomVariablesandJointDistributions192.1.4IndependenceandConditionalIndependence2:2.1.5QueryingaDistribution2.1.6ContinuousSpaces272.1.7ExpectationandVariance312.2Graphs342.2.1Nodesandedges342.2.2Subgraphs352.2.3Pathsandtrails36