Stat542: FAQs

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[Back to 542 Lecture]

Frequently Asked Questions
[Week 1: Introduction]
[Week 2: Linear Regression] [Week 3: Variable Selection and Regularization]
[Week 4: Regression Trees] [Week 5: Nonlinear Regression]
[Week 6: Clustering Analysis] [Week 7: Latent Structure Models]
[Week 9: Discriminant Analysis] [Week 10: Logistic Regression]
[Week 11: Support Vector Machine] [Week 12: Classification Trees]
[Week 13: Recommender System] [Week 14: Brief Introduction to Deep Learning]

  • Week 1: Introduction [Back_to_Index]
    • Degree of freedom for kNN [link]
    • Bayes error calculation for simulation study example I [link]
    • Questions Related to simulation study example II [link]
  • Week 2: Linear Regression [Back_to_Index]
    • Low R-square but significant F-test [link]
    • How to cheat with R-square [link]
    • Two toy examples [link]
    • Two-stage LS [link]

  • Week 3: Variable Selection and Regularization [Back_to_Index]
    • Why is elastic net called “elastic net” [link]
    • How does glmnet standardize the data [link]
    • Center/Scale dummy variables with glmnet [link]
    • Obtain Lasso coefficients using predict.glmnet [link]
    • DF of Ridge [link]
    • DF of Lasso [link]
    • Variable selection questions from a student [link]

  • Week 4: Regression Trees [Back_to_Index]
    • Question about pruning [link]
    • CV to find the best alpha or beta? [link]
    • The tree always decreases one by one as we prune it? [link]

  • Week 5: Nonlinear Regression [Back_to_Index]
    • gam vs mgcv [link]

  • Week 6: Clustering Analysis [Back_to_Index]

  • Week 7: Latent Structure Models [Back_to_Index]
    • Convergence of EM [link]

  • Week 9: Discriminant Analysis [Back_to_Index]
    • Semi-supervised learning [link]
    • Naive Bayes is a discriminant model or generative model? [link]

  • Week 10: Logistic Regression [Back_to_Index]
    • Logistic Regression with Large n and/or Large p [link]

  • Week 11: Support Vector Machine [Back_to_Index]
    • From Binary to multi-class [link]

  • Week 12: Classification Trees [Back_to_Index]

  • Week 13: Recommender System [Back_to_Index]

  • Week 14: Brief Introduction to Deep Learning [Back_to_Index]