In supervised Learning, the machine is trained with traning examples, in which each sample is a pair of features and a desired output value. That is, the machine is given right answer, and machine tries to figure out how to get the right answer out of the features.
- Finding relation between house properties (size, number of bedrooms, etc) and the price of the house.
- Distinguishing malignant (cancer) and benign (harmless).
- Given emails labeled as spam/not spam, learn a spam filter :
- Given a dataset of patients diagnosed as either having diabetes or not, learn to classify new patients as having diabetes or not.