title: Apply different transformations on features in machine learning
body: <p>I have features like Amount(20-100K$), Percent1(i.e. 0-1),Percent2(i.e.0-1). Here Amount values are between 20-100000 US dollars, and percent columns with decimals between 0-1. These features are positively skewed, so I applied log transformation on Amount, Yeo-Johnson using powertransformer on Percent1,Percent2 columns.</p>
  <p>Is it right to apply different transformations on columns, will it have an effect on model performance or should I same same transformation on all columns?</p>