1. supervised learning
- Modeling the relationship between input(X) and ouput(Y) variables
- Predicting or classifying the output variable(Y)
ㅁ regression: predict continuous output variables(float)
ㅁ classification: predict discrete output variables(integer)
2. unsupervised learning
- Modeling relationships between input variables(X)
e.g) Clustering analysis: group similar data
e.g) PCA: reducing the dimension of independent variables
3. reinforcement learning
- With numerous simulations, Learn to make current choices to maximize rewards in the future.
