diff --git a/content/appendix/02_errata.md b/content/appendix/02_errata.md index 5adf53a..b13b8bd 100644 --- a/content/appendix/02_errata.md +++ b/content/appendix/02_errata.md @@ -7,13 +7,11 @@ title: Errata - Chapter 1.4 (Models & Parameters) - slide 5/10: d-dimensional vector, not p-dimensional - Chapter 2.1 (Regression losses): Slide 1/5 sign in bullet point 4 - Chapter 2.2 (Deep Dive OLS): Slide 2/2 last lines in left column +- Chapter 3.6 (Naive Bayes): Slide 3/6: Missing exponents in figure - Chapter 4.3 (Simple Measures for Classification) - slide 6/9: Error in cost matrix - Chapter 4.4 (Perfomance Evaluation: Test Error) - slide 8/13: The variance of MSE decreases with test set size, not the mean of MSE - Chapter 4.7 (Classification measures): Slide 6/9 cost computation - Chapter 6.2 (CART: Growing a Tree) - slide 5/8: Wrong plot is displayed in video (axis wrong, points missing) -- Chapter 7.2 (Forests: Intro) - slides 7/8 and 8/8: Error in OOB error -- Chapter 7.4 (Forests: Feature importance) - slide 3/3: Error in permutation based variable importance -- Chapter 7.4 (Forests: Feature importance) - new slide 4/4: Improve explanation of MeanDecreaseAccuracy and MeanDecreaseGini - Chapter 11.6 (0-1 Loss): Slides 2/5 and 4/5 Errors in notation of conditional probability inside of expectation - Chapter 11.7 (Bernoulli Loss): Slides 9/10 and 10/10 Errors in Bernoulli Loss and Entropy Splitting Criterion - Chapter 11.12 (MLE2): Slide 2/5 wrong negative sign in NLL equation diff --git a/content/chapters/03_supervised_classification/03-03-classification-linear.md b/content/chapters/03_supervised_classification/03-03-classification-linear.md index 4c9eaba..027e7fd 100644 --- a/content/chapters/03_supervised_classification/03-03-classification-linear.md +++ b/content/chapters/03_supervised_classification/03-03-classification-linear.md @@ -9,7 +9,7 @@ Linear classifiers are an essential subclass of classification models. This sect ### Lecture video -{{< video id="wR43JOYxTZM" >}} +{{< video id="SkrQOtpD9d0" >}} ### Lecture slides diff --git a/content/chapters/03_supervised_classification/03-05-classification-discranalysis.md b/content/chapters/03_supervised_classification/03-05-classification-discranalysis.md index a639cd4..09b8f4c 100644 --- a/content/chapters/03_supervised_classification/03-05-classification-discranalysis.md +++ b/content/chapters/03_supervised_classification/03-05-classification-discranalysis.md @@ -9,7 +9,7 @@ Discriminant analysis is a generative approach toward constructing a classifier. ### Lecture video -{{< video id="inIhdMwQ4Ik" >}} +{{< video id="WHQLS9PBLig" >}} ### Lecture slides diff --git a/content/chapters/03_supervised_classification/03-06-classification-naivebayes.md b/content/chapters/03_supervised_classification/03-06-classification-naivebayes.md index f308731..f7e169b 100644 --- a/content/chapters/03_supervised_classification/03-06-classification-naivebayes.md +++ b/content/chapters/03_supervised_classification/03-06-classification-naivebayes.md @@ -9,7 +9,7 @@ Naive Bayes is a generative approach based on an assumption of conditional indep ### Lecture video -{{< video id="bvAYZsIt04U" >}} +{{< video id="TJ0ZSAyIi_c" >}} ### Lecture slides