Data preprocessing

Data preprocessing typically involves (some of) the following steps:

1. Data cleaning
2. Feature scaling
   1. Normalization
   2. Standardization
3. Decorrelation and whitening
4. Dimensionality reduction

"Efficient BackProp" paper by LeCun, describes the strategy of pre-processing data as:

1. shift the data so that its mean is 0
2. de-correlate the data
3. normalize the data so each input has a variance of ~1

stats++

In stats++, data preprocessing is handled through a Preprocessor object:

Preprocessor