10. Logistic Regression (IB533 2022.09)

Unit Outlines：

■ Logistic Regression

§ method：glm(… , family = binomial)

§ model fitting & prediction

§ interpreting the coefficients

■ Measures of Model Accuracy

§ Accuracy, Sensibility, Specificity

§ Confusion Matrix and Accuracy Metrics

§ ROC and AUC

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Notebooks：

◆ UNIT10A： Logistic Regression (unit10A.html)

◆ UNIT10B：LogisticReg. – The Coefficients (unit10B.html)

◆ UNIT10C LogisticReg. – Model Accuracy (unit10C.html)

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Google Drive： 

◆ Course Material : [  ~/ib533/ ]

◆ Unit10:  [ ~/ib533/10_LogisticReg/ ]

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Unit10  Personal Assignments ： Due at  2022/12/05 (Sun) 23:59

Register to edX and sign in to MIT’s  The Analytic Edges course with audit option

Finish Unit3-1  Modeling the Expert: An Introduction to Logistic Regression

Do the quiz in a Rmd, knit the HTML  and

upload it to 【 ~/person/10_AnalEdge 】with filename “<student.id>_AnalEdge.html“

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Video Recording：

◆ Unit10 Video Recording

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References :

◆  Portal of Big Data BA Platform

◆  R: Self Learning Roadmap

◆  John Hopkins: R Programming online course

◆  John Hopkins: R Programming eBook

◆  Harvard: Data Science online course

◆  Harvard: Data Science ebook

◆  From Data to Viz

◆  Probability Cheat Sheet (pdf)

◆  Intro. Probability and Statistics Using R (IPSUR)

◆  Statistical Analysis Using R, UCLA (URL)

◆  CLUSTER ANALYSIS IN R: PRACTICAL GUIDE (URL)

◆  Principal Component Methods in R: Practical Guide (URL)