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OversamplingLogistic RegressionPredictive Modellingregression
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강의 계획 - 이 강좌에서 배울 내용

1

1

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Course Overview and Logistics

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1개 동영상 (총 1분), 6 개의 읽기 자료
1개의 동영상
6개의 읽기 자료
What You Learn in This Course5m
Learner Prerequisites1m
Using Forums and Getting Help10m
Access SAS Software for this Course10m
Set Up Data for This Course (REQUIRED) 30m
About the Demos and Practices in this Course10m
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Understanding Predictive Modeling

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15개 동영상 (총 34분), 1 개의 읽기 자료, 6 개의 테스트
15개의 동영상
Introduction19
Goals of Predictive Modeling1m
Terms for Elements in Predictive Modeling49
Basic Steps of Predictive Modeling2m
Applications of Predictive Modeling1m
Demonstration Scenario: Target Marketing for a Bank1m
Demo: Examining the Code for Generating Descriptive Statistics and Frequency Tables2m
Introduction21
Data Challenges6m
Analytical Challenges2m
Separate Sampling1m
Avoiding the Optimism Bias: Honest Assessment2m
Splitting the Data for Model Training and Assessment3m
Demo: Splitting the Data5m
1개의 읽기 자료
Summary10m
6개 연습문제
Practice: Exploring the Bank Data for the Target Marketing Project20m
Practice: Exploring the Veterans' Organization Data Used in the Practices20m
Question 1.015m
Question 1.025m
Question 1.035m
Practice: Splitting the Data20m
2

2

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Fitting the Model

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18개 동영상 (총 54분), 1 개의 읽기 자료, 4 개의 테스트
18개의 동영상
Introduction22
Understanding the Logistic Regression Model2m
Constraining the Posterior Probability Using the Logit Transformation1m
Understanding the Fitted Surface1m
Interpreting the Model by Calculating the Odds Ratio3m
Understanding Logistic Discrimination1m
Estimating Unknown Parameters Using Maximum Likelihood Estimation2m
Interpreting Concordant, Discordant, and Tied Pairs1m
Using PROC LOGISTIC to Fit Logistic Regression Models24
Demo: Fitting a Basic Logistic Regression Model, Part 18m
Demo: Fitting a Basic Logistic Regression Model, Part 212m
Scoring New Cases26
Demo: Scoring New Cases7m
Introduction16
Understanding the Effect of Oversampling53
Understanding the Offset1m
Demo: Correcting for Oversampling6m
1개의 읽기 자료
Summary10m
4개 연습문제
Question 2.015m
Question 2.025m
Practice: Fitting a Logistic Regression Model20m
Fitting the Model Review30m
3

3

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Preparing the Input Variables, Part 1

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26개 동영상 (총 76분)
26개의 동영상
Introduction22
Reasons for Missing Data2m
Complete Case Analysis1m
Methods for Imputing Missing Values2m
Missing Value Imputation with Missing Value Indicator Variables3m
Demo: Imputing Missing Values4m
Cluster Imputation1m
Introduction25
Problems Caused by Categorical Inputs4m
Solutions to Problems Caused by Categorical Inputs39
Linking to Other Data Sets56
Collapsing Categories by Thresholding53
Collapsing Categories by Using Greenacre's Method3m
Demo: Collapsing the Levels of a Nominal Input, Part 16m
Demo: Collapsing the Levels of a Nominal Input, Part 210m
Replacing Categorical Levels by Using Smoothed Weight-of-Evidence Coding2m
Demo: Computing the Smoothed Weight of Evidence4m
Introduction20
Problem of Redundancy2m
Variable Clustering Method1m
Understanding Principal Components5m
Divisive Clustering3m
PROC VARCLUS Syntax1m
Selecting a Representative Variable from Each Cluster1m
Demo: Reducing Redundancy by Clustering Variables8m
9개 연습문제
Question 3.015m
Practice: Imputing Missing Values20m
Question 3.025m
Question 3.035m
Question 3.045m
Practice: Collapsing the Levels of a Nominal Input20m
Practice: Computing the Smoothed Weight of Evidence20m
Question 3.055m
Practice: Reducing Redundancy by Clustering Variables20m
4

4

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Preparing the Input Variables, Part 2

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23개 동영상 (총 92분), 1 개의 읽기 자료, 12 개의 테스트
23개의 동영상
Detecting Nonlinear Relationships4m
Demo: Performing Variable Screening, Part 15m
Demo: Performing Variable Screening, Part 24m
Univariate Binning and Smoothing2m
Demo: Creating Empirical Logit Plots10m
Remedies for Nonlinear Relationships2m
Demo: Accommodating a Nonlinear Relationship, Part 16m
Demo: Accommodating a Nonlinear Relationship, Part 27m
Introduction26
Specifying a Subset Selection Method in PROC LOGISTIC1m
Best-Subsets Selection54
Stepwise Selection2m
Backward Elimination1m
Scalability of the Subset Selection Methods in PROC LOGISTIC2m
Detecting Interactions2m
BIC-based Significance Level2m
Demo: Detecting Interactions7m
Demo: Using Backward Elimination to Subset the Variables4m
Demo: Displaying Odds Ratios for Variables Involved in Interactions3m
Demo: Creating an Interaction Plot3m
Demo: Using the Best-Subsets Selection Method3m
Demo: Using Fit Statistics to Select a Model9m
1개의 읽기 자료
Summary of Preparing the Input Variables, Parts 1 and 210m
12개 연습문제
Question 3.065m
Practice: Performing Variable Screening20m
Practice: Creating Empirical Logit Plots20m
Question 3.075m
Question 3.085m
Question 3.095m
Practice: Using Forward Selection to Detect Interactions20m
Question 3.105m
Practice: Using Backward Elimination to Subset the Variables20m
Question 3.115m
Practice: Using Fit Statistics to Select a Model20m
Preparing the Input Variables Review30m

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