Single-label multiclass classification random forest python
Method of (One Hot Encoder) applies to category variables, and category variables have no size relationship.For the price variable,I suggest you use OrinalEncoder.Sklearn is a good package for machine.like, sklearn learning.preprocessing.OneHotEncoder or sklearn.preprocessing.OrdinalEncoder
I am pretty new to machine learning and I am currently dealing with a dataset in the format of a csv file comprised of categorical data. As a means of preprocessing, I One Hot Encoded all the variables in my dataset. 
At the moment I am trying to apply a random forest algorithm to classify the entries into one of the 4 classes. My problem is that I do not understand exactly what happens to these One Hot Encoded variables. How do I feed them to the algorithm? Is it able to make the difference between buying_price_high, buying_price_low (One Hot Encoded from buying_price)? 
I One Hot Encoded the response variable as well.