SASMinerPredictiveModeling学习课程

1、Contents01. Presentation sub title01-1. Presentation title01-2. Presentation title02. Presentation sub title04. Link Analysis02-1. Presentation title02-2. Presentation title03-1. Presentation title03-2. Presentation title03. Association Analysis03-1. Presentation title03-2. Presentation title第1页/共15

2、页第一页，编辑于星期六：十九点 五十分。Overview of Modeling CaseOur user-friendly and functional search engine helps you locate the right templates, effectively saving your time.Slide main titleDesign inspiration For presentationTarget: BADA financial company wants to build a model to predict whether an applicant will

3、 default. 1 indicates that the client defaulted on the loan or is seriously delinquent; 0 indicates the opposite.Personal StatusvDEBTINCvJOBvVALUEvREASONvYOJCredit RecordsvCLAGEvCLNOvDELINQvDEROGvNINQvMORTDUEvLOAN第2页/共15页第二页，编辑于星期六：十九点 五十分。Slide main titleDesign inspiration For presentationPersonal

4、StatusCredit Records DEBTINC-Debt-to-income ratio JOB*-Occupational categories VALUE-Value of the current property REASON*-DebtCon for debt consolidation; HomeImp for home improvement YOJ-Years at the applicants current job CLAGE-Age of the oldest credit line CLNO-Number of credit lines DELINQ*-Numb

5、er of delinquent credit lines DEROG-Number of major derogatory reports NINQ-Number of recent credit inquiries MORTDUE-Amount due on the existing mortgage LOAN-Amount requested for the loan BAD-1 indicates that client defaulted on the loan or is seriously delinquent; 0 indicates the opposite.Target第3

6、页/共15页第三页，编辑于星期六：十九点 五十分。Slide main titleDesign inspiration For presentation第4页/共15页第四页，编辑于星期六：十九点 五十分。Clustering ToolsPart 2 of 4第5页/共15页第五页，编辑于星期六：十九点 五十分。Problem FormulationA baseball manager wants to identify and group players on the team who are very similar with respect to several statistics o

7、f interest. The manager simply wants to identify different groups of players. The manager also wants to learn what differentiates players in one group from players in a different group.Clustering ToolsDesign inspiration For presentationCareer PerformancePerformance in 1968Below average: 1 and 3 Abov

8、e Average: 2 and 4Below average: 1 and 2Above Average: 3 and 4RookieYoung and TalentedAlmostRetiredElite第6页/共15页第六页，编辑于星期六：十九点 五十分。Association AnalysisPart 3 of 4第7页/共15页第七页，编辑于星期六：十九点 五十分。Association AnalysisDesign inspiration For presentation A store wants to understand which of its products tend

9、to be purchased together. Its data set lists 200 rules in the input data set. Each rule of the data set represents a customer purchase item A first and item B second.Problem FormulationThe support percentage for A = B is the percentage of all customers who purchased both A and B. Support is a measur

10、e of how frequently the rule occurs in the database.Support(%)01The confidence percentage for A = B is the percentage of all customers who purchased both A and B, divided by the number of customers who purchased A.Confidence(%)02The lift of A = B measures the strength of the association. For example

11、, if lift is 2 for A = B, then a customer who purchased A is twice as likely than a customer chosen at random to purchase B.Lift03第8页/共15页第八页，编辑于星期六：十九点 五十分。Association AnalysisDesign inspiration For presentationLift: 2.38Support: 36.56%Confidence: 82.62%artichoke = HeinekenHeineken = crackercracker

12、 = HeinekenIce-cream = cokecoke = ice-creamConfidence: 68.60%avocado = HeinekenSupport: 24.88%Lift: 1.14第9页/共15页第九页，编辑于星期六：十九点 五十分。Association AnalysisDesign inspiration For presentationPut Heineken shelf close to the artichoke.Bundle Heineken with crackers; bundle ice-cream with coke. Suggestions第1

13、0页/共15页第十页，编辑于星期六：十九点 五十分。Link AnalysisPart 4 of 4第11页/共15页第十一页，编辑于星期六：十九点 五十分。Link AnalysisDesign inspiration For presentationProblem FormulationWeb Log Data SetYou sell books and other publications from your website. You web log data contains information about the navigation patterns that visitors

14、 make within your website. You want to examine the files that are requested. In addition, you want to determine what paths visitors take when they make a purchase.第12页/共15页第十二页，编辑于星期六：十九点 五十分。Link AnalysisDesign inspiration For presentationthe most frequent links which links from Cart.jsp are:Confirm.jsp, Summary.jsp, Billing.jsp, and Shipping.jsp.Items Constellation PlotOther frequent links to Cart.jsp are:Produict.jsp, Home.jsp, Department.jsp, and Subcategory.jsp.Undi