Amit Rajan

Tag

Classification

16 notes

2022 9

  1. Linear Models for Classification - The Laplace Approximation & Bayesian Logistic Regression Bishop · Chapter 4 — Linear Models for Classification Bishop
  2. Linear Models for Classification - Probabilistic Discriminative Models Bishop · Chapter 4 — Linear Models for Classification Bishop
  3. Linear Models for Classification - Probabilistic Generative Models (Maximum Likelihood Solution) Bishop · Chapter 4 — Linear Models for Classification Bishop
  4. Linear Models for Classification - Probabilistic Generative Models Bishop · Chapter 4 — Linear Models for Classification Bishop
  5. Linear Models for Classification - The Perceptron Algorithm Bishop · Chapter 4 — Linear Models for Classification Bishop
  6. Linear Models for Classification - Fisher’s Linear Discriminant Bishop · Chapter 4 — Linear Models for Classification Bishop
  7. Linear Models for Classification - Least Squares for Classification Bishop · Chapter 4 — Linear Models for Classification Bishop
  8. Linear Models for Classification - Discriminant Functions (Part 2) Bishop · Chapter 4 — Linear Models for Classification Bishop
  9. Linear Models for Classification - Discriminant Functions Bishop · Chapter 4 — Linear Models for Classification Bishop

2018 7

  1. Logistic Regression Logistic Regression: Derivation Note
  2. Performance Metrics for Classification Algorithms Performance Metrics for Classification Algorithms Note
  3. Naive Bayes Classifier Classification Note
  4. Classification: Applied Exercises ISLR · Chapter 4 — Classification ISLR
  5. Classification: Conceptual Exercises ISLR · Chapter 4 — Classification ISLR
  6. Linear Discriminant Analysis ISLR · Chapter 4 — Classification ISLR
  7. Logistic Regression ISLR · Chapter 4 — Classification ISLR