Statistical Learning with Python - Statistical Learning: 4.7 Gaussian Discriminant Analysis (Many Variables)

Statistical Learning, featuring Deep Learning, Survival Analysis and Multiple Testing Trevor Hastie, Professor of Statistics and Biomedical Data Sciences at Stanford University - https://statistics.stanford.edu/people/trevor-j-hastie Robert Tibshirani, Professor of Statistics and Biomedical Data Sciences at Stanford University - https://statistics.stanford.edu/people/robert-tibshirani Jonathan Taylor, Professor Statistics at Stanford University - https://statistics.stanford.edu/people/jonathan-taylor You are able to take Statistical Learning as an online course on EdX, and you are able to choose a verified path and get a certificate for its completion. You can choose to take the course in R (https://www.edx.org/course/statistica) or in Python (https://www.edx.org/learn/data-analysis-statistics/stanford-university-statistical-learning-with-python) For more information about courses on Statistics, you can browse our Stanford Online Catalog: https://stanford.io/3QHRi72 0:00 Linear Discriminant Analysis when p 1 3:17 Illustration: p = 2 and K = 3 classes 5:27 Fisher's Iris Data 7:10 Fisher's Discriminant Plot 11:00 LDA on Credit Data 13:45 Types of errors 15:04 Varying the threshold