商務(wù)智能錄屏2020ch5數(shù)值預(yù)測

11IntroductionChapter5Numeric?He?HePrinciplesandApplicationsofBusiness Chap5：NumericPrinciplesandApplicationsofChap5：Numeric§Basic§Typical§Model§2Chap5：NumericPrinciplesandApplicationsChap5：NumericWhatIsNumericModelcontinuous-valuedfunctions,i.e.,unknownormissingvalues§PredictionissimilartoFirst,constructaSecond,usemodeltopredictunknown§Predictionisdifferentfrom

ClassificationreferstopredictcategoricalclassPredictionmodelscontinuous-valued3Chap5：NumericPrinciplesandApplicationsChap5：NumericClassificationvs.NumericIndependent（自變量e324767…………

372763Continuous4Chap5：NumericPrinciplesandApplicationsofChap5：NumericPrediction§TwokindsofLazyand§Majormethodforprediction:LinearandmultipleNon-linearModeltree,regression5Chap5：NumericPrinciplesandApplicationsofChap5：NumericKnearest6Thek-NearestNeighbor Allinstancescorrespondtopointsinthen-D ThenearestneighboraredefinedintermsofEuclidean Thetargetfunctioncouldbediscrete-orreal- Forcontinuous-valuedtargetfunctions，Calculatethemeanvaluesoftheknearestneighborsv'

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7Application：mender8Chap5：NumericPrinciplesandApplicationsChap5：NumericCollaborativeFiltering:AItems: 3522352213…

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..Unknownf:UxI9PrinciplesandApplicationsofBusiness CollaborativeFilteringRoad§User-UserIdentifylike-mindedMemory-based:§Item-ItemIdentifybuying

Chap5：NumericChap5：NumericPrinciplesandApplicationsofChap5：NumericUser-UserChap5：NumericPrinciplesandApplicationsofChap5：Numeric§SimilarusershavesimilarIfuu’,thenforallo’s,f(u,o)§Usersimilarity(ZhangSanvs.LiSupposeZhangSanandLiSiviewedsimilarmoviesinthepastsixmonths…IfZhangSanlikedthepaper,LiSiwillliketheUser-UserSimilarity:Q1:Q1:HowtoQ2:HowtoChap5：NumericPrinciplesandApplicationsChap5：NumericHowtoMeasure§Pearsoncorrelationcoefficient（相關(guān)系數(shù)法

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Chap5：Numeric Chap5：NumericPredictratingforagivenuser-itempairasaweightedoversimilaritemsthathe4?32sij4?32rajisimilar PrinciplesandApplicationsofBusiness Chap5：Numericprediction §LinearY=0+1X+Parameters:0,Randomvariable:N(0,

Chap5：NumericPrinciplesandApplicationsChap5：Numeric

PrinciplesandApplicationsofBusiness

Chap5：Numeric§Estimateparametersbasedontraining?iaUsingtheleastsquarescriteriontotheknownvaluesofy1)(x2,y2)

Chap5：NumericPrinciplesandApplicationsChap5：NumericEstimating§leastsquares最小二乘法 minimize

2(y?)2 nb

(xix)(yiynn2(xix2 1aybx

nn

b

nnx和ymeanvaluesofXandsxx稱為x的校正平方和,sxyChap5：NumericPrinciplesandApplicationsofChap5：NumericLinear Chap5：NumericPrinciplesandApplicationsChap5：Numeric22 22Modelvalidation

i (yi?i n §回歸平方和

(

y)2n 總離差平方和 n (yy)2

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R2SSR1SSE

R2

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Chap5：Numeric H1: 可以證明在H0成立的情況下由下式定義的F符合F(1,n-2)分F SSE/(n 得臨界值F(1,n-2)，若由上式計算的F0>F(1,n-2)則因變量PrinciplesandApplicationsofBusiness

Chap5：Numeric 數(shù)a和b /(n xbSS2 bS

2 E an2 a H0: H1: (若tb>t(n-2)， 同時可以計算出P值（pvalue），一般以P0.05<0.01Chap5：NumericPrinciplesandChap5：Numeric§Multiple~N(0,§nobservationxi1xi2xik，yi)，i=1,2,n。Basedontheseobservations,estimateparameters：? b0b1xi...bkPrinciplesandApplicationsofBusiness

Chap5：Numeric§Manynonlinearfunctionscanbetransformedintothe

§y=aebx，可以通過兩邊取對數(shù)變換為§y=a+blgxX=lgx，則有ya+b§Commonlysolvedbyusingofstatisticalsoftwarepackages,suchasSAS,SPSS,andS-Plus§Weka:?Data:EvaluatingNumeric§SimilartoTrainingset,test§DifferentfromQualitymeasurebyerrorrateisnot均方誤差(mean-squared均誤差(rootmean-squared平均絕