How to predict product price range using machine learning algorithms I would like to run thru regression algorithms(linear, SVM, Random forest, Xgboost) thru historical data to predict the price range of a product. 

To get the price range am going to use top predict value as upper bound and next best value as lower bound). 

Ex: Product a price range preicttion - $1000 to $5000. 

$5000 is from top predicted price. 
$1000 is from next best-predicted price. 


Is my approach correct? 

Yet to receive data, so do not have much data sample to provide.

Please suggest.
If in your dataset you have two columns for the minimum and maximum value as columns n-1 and n, you can train the dataset for n-1 columns, where n-1th column is your dependent value, then for predicting nth column, the nth column would be your dependent value and n-1 others independent.