ML 6.3Lesson outlineLesson 3 of 3 in Module 6
Generative and Discriminative Models: LDA and QDA
Classify by modelling each class as a Gaussian, and see why shared or separate covariances give linear or curved boundaries.
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Lesson outline: Generative and Discriminative Models: LDA and QDA
In this lesson12 parts
- 01A species from four measurements
- 02The Palmer penguins
- 03The most common species
- 04Model each species, then apply Bayes
- 05Means, covariances and priors
- 06Maximum likelihood again
- 07Fitting is averaging
- 08Scoring one penguin, and where the boundary bends
- 09Measuring it
- 10Fisher's projection, and Naive Bayes as the diagonal case
- 11What the parameters cost
- 12Code, the sealed birds, recap and bridge
Builds on
This lesson stands on its own. These go deeper into what it uses.