Machine Learning No.9: Dimensionality reduction

1. Principal component analysis algorithm

data preprocessing

2. choosing the number of principal components

3. reconstruction from compressed representation

4. Application of PCA

   - compression

　　- reduce memory/dist needed to store data

　　- speed up learning algorithm

   - visualization

bad use of PCA: to prevent overfitting