Scalling
Standard scalar:
Subtract the mean and scale by the sttddev
Minmax scaling:
transforms each value to a given range
Nomralization:
Log/ power transformation:
- non linear
How to scale data:
- Use the Training data to find the scaling parameters
- Estimates of mean and variance
- The , apply the transformation
When to scale data:
- When using linear model with regulariztion
- When using linear models without regularization
- Model converge faster
- Don’t need to scale if need to interpret in original units
- When using neural networks
- Gradient deseent
- When using nearest-neighbor type algorithms
Regularized regression
Data :