Machine Learning No.9: Dimensionality reduction

1. Principal component analysis algorithm

data preprocessing

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2. choosing the number of principal components

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3. reconstruction from compressed representation

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4. Application of PCA

   - compression

  - reduce memory/dist needed to store data

  - speed up learning algorithm

   - visualization

bad use of PCA: to prevent overfitting

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