Course Outline
Introduction
|
Slides |
Formal definition of classification, Linear discriminant analysis (LDA), Quadratic discriminant analysis (QDA)
|
Slides |
QDA, Principal Component Analysis (PCA)
|
Lecture 3 |
PCA, Fisher's Discriminant Analysis (FDA)
|
Lecture 4 |
Logistic Regression
|
Lecture 5 |
Logistic Regression, Perceptron |
Lecture 6 |
Backpropagation |
Lecture 7 |
Radial Basis Function Networks
|
Lecture 8 |
Stein’s unbiased risk estimate (sure)
|
Lecture 9 |
Weight decay |
Lecture 10 |
Hard margin svm |
Lecture 11 |
Soft margin svm |
Lecture 12 |
Lecture 13 |
Lecture 13 |
Supervised PCA, Decision tree |
Lecture 14 |
Decision Tree, KNN |
Lecture 15 |
Boosting |
Lecture 16 |