Supervised Learning Given training data ={(x1,y1),(x2,y2),..,(XN,yN)}where yi is the corresponding label of data xi,supervised learning learns the mapping function Y F(X|0),or the posterior distribution P(Y X). Dependent variable:PLAY ·Supervised problems Play Don't Play 5 -Classification OUTLOOK Regression sunny overcast rain Learn to Rank Play 2 Play Play 3 Tagging Don't Play 3 Don't Play 0 Don't Play 2 HUMIDITY WINDY <=70 >70 TRUE FALSE Play 2 Play 0 Play 0 Play 3 Don't Play 0 Don't Play 3 Don't Play 2 Don't Play 0Given training data 𝑋 = x1, y1 , x2, y2 , … , xN, yN where 𝑦𝑖 is the corresponding label of data 𝑥𝑖 , supervised learning learns the mapping function 𝑌 = 𝐹(𝑋|𝜃), or the posterior distribution 𝑃 𝑌 𝑋 . • Supervised problems – Classification – Regression – Learn to Rank – Tagging – …… Supervised Learning