11月 12, 2016

演算法筆記 | Machine Learning (Stanford) Lecture 2 史丹佛大學機器學習




m = number of training examples
x = input variables/features
y = output/target variables
(x,y) = training example
(xi,yi) = ith training example

h = hypothesis


  • continuous: regression
  • discrete: classification