note 7: gaussian discriminant analysis, qda, lda
people.eecs.berkeley.edu · 1,698 words · saved by 1 readers
N/A
36 Jonathan Richard Shewchuk 7 Gaussian Discriminant Analysis, including QDA and LDA GAUSSIAN DISCRIMINANT ANALYSIS Fundamental assumption: each class has a normal distribution [a Gaussian]. ! 2 1 kx µk2 X ⇠ N(µ, ) : f (x) = p exp . [µ & x = vectors; = scalar; d = dimension] ( 2⇡ )d 2 2 For each class C, suppose we know mean µC and variance 2C , yielding PDF fX|Y=C (x),…
related reading
- Gregory Gundersengregorygundersen.com
- note 6: bayes decision rulepeople.eecs.berkeley.edu
- Naive Bayes Classifiers - GeeksforGeeksgeeksforgeeks.org
- catoni_draft2.pdfocatoni.perso.math.cnrs.fr
- Bayes-Optimal Strategiesemergentmind.com
- Logs, Tails, Long Tails – Ryan Moulton's Articlesmoultano.wordpress.com
- Classificationfairmlbook.org
- An illustrative introduction to Fisher's Linear Discriminant - Thalles' blogsthalles.github.io
- Normal Approximation to the Posterior Distribution | Bounded Rationalitybjlkeng.github.io
- Learning to be Bayesian without Supervisionpapers.nips.cc
- bayesian - Bayes regression: how is it done in comparison to standard regression? - Cross Validatedstats.stackexchange.com
- A Course in Machine Learningciml.info