I was going through the ML self study course on CloudXLab.
Can you help me understand how to handle skewed data in the below cases?
I have to perform regression on data with 9 features:
- One of the features is skewed, but the target variable is not skewed. Do we need to apply transformation (log) on Skewed data column or on all the features?
- One of the features is skewed and the target variable is also skewed. Do we need to apply transformation (log) on Skewed data column or on the target variable?
- If data skew is observed in one feature and I apply log transformation on the feature. Can I apply Standardization or Normalization on other features considering the fact that for one of the feature, Log transformation is applied?