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Predictive Modeling with Logistic Regression using SAS

This course covers predictive modeling using SAS/STAT software with emphasis on the LOGISTIC procedure. This course also discusses selecting variables and interactions, recoding categorical variables based on the smooth weight of evidence, assessing models, treating missing values, and using efficiency techniques for massive data sets. You learn to use logistic regression to model an individual's behavior as a function of known inputs, create effect plots and odds ratio plots, handle missing data values, and tackle multicollinearity in your predictors. You also learn to assess model performance and compare models.

状态:Regression Analysis
状态:Predictive Modeling
中级课程小时

精选评论

RM

5.0评论日期:Jun 14, 2021

Thank you so much to the instructor, Michael J Patetta for teaching this course!

SS

5.0评论日期:Apr 10, 2021

Great training sets of problems. Good guidance & teaching.

MC

5.0评论日期:Dec 30, 2022

Very completed and deep knowledge shared with very friendly ways, explained the knowledge very clearly. Also the practices help me to understand the knowledge better.

所有审阅

显示:12/12

K
2.0
评论日期:Oct 26, 2022
Suhaimi Chan
5.0
评论日期:Sep 28, 2021
Vipul Patki
5.0
评论日期:May 16, 2021
Hamid Fotouhi
5.0
评论日期:Jul 12, 2022
Deleted Account
5.0
评论日期:Jul 29, 2021
Mia CAO
5.0
评论日期:Dec 30, 2022
Rugshana Madatt
5.0
评论日期:Jun 15, 2021
SURAJ RAJU SHARMA
5.0
评论日期:Apr 11, 2021
UmamaheswaraRao Putrevu
5.0
评论日期:Dec 27, 2022
NOEL ROJAS VILLATORO
4.0
评论日期:Feb 4, 2022
Kartik Khandelwal
2.0
评论日期:Jan 27, 2021
Ravi Shankar Singh
1.0
评论日期:Jan 12, 2021