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1、https://github.com/soulmachine/machine-learning-cheat-sheetsoulmachine@gmail.comMachineLearningCheatSheetClassicalequations,diagramsandtricksinmachinelearningFebruary12,2015ii©2013soulmachineExceptwhereotherwisenoted,ThisdocumentislicensedunderaCreativeCommonsAttribution
2、-ShareAlike3.0Unported(CCBY-SA3.0)license(http://creativecommons.org/licenses/by/3.0/).PrefaceThischeatsheetcontainsmanyclassicalequationsanddiagramsonmachinelearning,whichwillhelpyouquicklyrecallknowledgeandideasinmachinelearning.Thischeatsheethasthreesignificantadvantag
3、es:1.Strongtyped.Comparedtoprogramminglanguages,mathematicalformulasareweaklytyped.Forexample,Xcanbeaset,arandomvariable,oramatrix.Thiscausesdifficultyinunderstandingthemeaningofformulas.Inthischeatsheet,Itrymybesttostandardizesymbolsused,seesection§.2.Moreparentheses.Inm
4、achinelearning,authorsarepronetoomitparentheses,bracketsandbraces,thisusuallycausesambiguityinmathematicalformulas.Inthischeatsheet,Iuseparentheses(bracketsandbraces)atwheretheyareneeded,tomakeformulaseasytounderstand.3.Lessthinkingjumps.Inmanybooks,authorsarepronetoomit
5、somestepsthataretrivialinhisoption.Butitoftenmakesreadersgetlostinthemiddlewayofderivation.AtTsinghuaUniversity,May2013soulmachineiiiContentsContents....................................v2.5.3MultivariateStudent’st-distribution...............10Notation....................
6、.................xiii2.5.4Dirichletdistribution.........102.6Transformationsofrandomvariables...111Introduction.............................12.6.1Lineartransformations.......111.1Typesofmachinelearning............12.6.2Generaltransformations......111.2Threeelementsofamac
7、hinelearning2.6.3Centrallimittheorem........13model.............................12.7MonteCarloapproximation...........131.2.1Representation..............12.8Informationtheory..................141.2.2Evaluation.................12.8.1Entropy....................141.2.3Optim
8、ization...............22.8.2KLdivergence..............141.3Somebasicconcepts.................22.8.3Mutu
