title: Scaling data with large range in Machine learning preprocessing
body: <p>I am very much new to Machine Learning.
  And I am trying to apply ML on data containing nearly 50 features. Some features have range from <strong>0 to 1000000 and some have range from 0 to 100</strong> or even less than that. Now when I use feature scaling by using <strong>MinMaxScaler</strong> for range <strong>(0,1)</strong> I think features having large range <strong>scales down to very small values</strong> and this might affect me to give good predictions.</p>
  
  <p>I would like to know if there is some efficient way to do scaling so that all the features are scaled appropriately. </p>
  
  <p>I also tried standared scaler but accuracy did not improve.
  Also Can I use different scaling function for some features and another for remaining features.</p>
  
  <p>Thanks in advance!</p>