Predictive Modeling Using Logistic Regression

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SAS:Predictive Modeling Using Logistic Regression
For Your Information Table of contents Course Description Prerequisites 。4垂 V11 Chapter 1 Predictive Modeling…………… 1-1 1.1 Introduction 1-3 Demonstration: Exploring the Data............... 1-10 1.1 Analytical Challenges.......... …1-13 1.2 Chapter Summary……………… 1-20 Chapter 2 Fitting the model 2-1 2.1 The model Demonstration Introduction to the logistic procedure 2-16 Demonstration: Scoring new cases.............................2-28 2.2 Adjustments for Oversampling 2-29 Demonstration: Correcting for Oversampling …2-33 Exercises 2.3 Chapter Summary........... ········.:···:········· 2.4 Solutions…… …2-40 Solutions to exercises 2-40 Solutions to Student Activities(Polls/Quizzes) 2-46 Chapter 3 Preparing the Input Variables ... ■■口■■■■■■酯■■口■■■■m■ 3-1 Missing Valu Demonstration: Imputing Missing Values 3-10 Exercises 3.2 Categorical Inputs …3-14 For Your information Demonstration: Clustering Levels of Categorical Inputs........3-18 Exercises 3-25 3. 3 Variable Clustering …13-26 Demonstration: Variable Clustering 3-35 Exercises… 3.4 Variable Screening... 3-45 Demonstration: Variable Screening…… 3-47 Demonstration: Empirical Logit Plots Exercises ·面 3-58 Demonstration: Accommodating Nonlinearities ,3-61 3.5 Subset Selection 3-68 Demonstration: Automatic Subset Selection 3-73 Exercises ······· 3-87 3.6 Chapter summary 3-88 3.7 Solutions.. 3-89 Solutions to exercises 3-89 o Solutions to student Activities(Pol/ Quizzes).……… 3-109 Chapter 4 Measuring Classifier Performance 4-1 4 1 Honest assessment Demonstration Honest model assessment 4.2 Misclassification 4-36 Demonstration: Assessing Classifier P 4-43 Exercises 4-50 4.3 Allocation rules 4-51 Demonstration: Using Profit to Assess Fit.………… 4-56 4.4 Overall Predictive power 4-60 Demonstration: Calculating the k-s and c statistics For Your Information 4.5 Model selection Plots 4-67 Demonstration: Comparing and Evaluating Models 4.6 Chapter Summary 4-81 4.7 Solutions.… Solutions to exercises 4-82 Solutions to Student activities (Polls/Quizzes)............ .4-87 Appendix a Additional Resources..... A-1 A 1 Scoring new Cases in sas 8 A-2 A2 Automatic Score Code generation A-4 A3 Correcting for Oversampling in SAs 8..... A-8 A 4 Correcting the Intercept in the Score Code Generator A-11 A.5 Sampling Weights A-14 Demonstration: Sampling Weights…… A-15 A6 Cluster Imputation Using PRoC Fastclus △-18 A 7 %ASSESS Macro... A-19 C A. 8 %FITANDSCORE Macro A-22 △.9 References… A-24 Appendix B Index B-1 For Your information Course Description This course covers predictive modeling using SAS!STAT software with emphasis on the LOgistic procedure. This course also discusses selecting variables, assessing models, treating missing values, and using efficiency techniques for massive data sets To learn more Ssas For information on other courses in the curriculum contact the sas education Divisionat1-800-333-7660,orsende-mailtotraining(@sas.com.Youcanalso find this information on the Web at support. sas. com/training/ as well as in the Education Training Course Catalog sas For a list of other Sas books that relate to the topics covered in this Course notes, USa customers can contact our Sas Publishing department at 1-800-727-3228orsende-mailtosasbookl@sas.com.Customersoutsidethe Publishing USA, please contact your local SAS office Also, see the Publications Catalog on the Web at support. sas. com/pubs for a complete list of books and a convenient order for For Your Information Prerequisites Before attending this course, you should have experience executing SAs programs and creating SaS data sets, which you can gain from the SAS Programming I: Essentials course have experience building statistical models using sas software have completed a statistics course that covers linear regression and logistic regression, such as the Statistics I: Introduction to ANOVA, Regression, and Logistic Regression course ot for redistribution viii for your information ot for redistribution Chapter 1 Predictive Modeling 1.1 Introduction 13 Demonstration: Exploring the Data…… 110 1.1 Analytical Challenges 1-13 1.2 Chapter Summary. 120 ot for redistribution 1-2 Chapter 1 Predictive Modeling ot for redistribution

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puluowangsi12345 资源不错,谢谢分享
2016-04-25
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wang112358 是数据分析师的参考教材之一,英文原版,讲述了逻辑回归的相关知识。
2015-04-20
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sinat_20566263 超好的资源,找了好久终于找到了
2014-11-15
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robertpeter2008 不错,英文原版
2014-09-14
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