## RandomForestRegressor leads to KeyError: ‘squared_error’

I am trying to predict house prices in the Cali housing data set with a random forest. I do not understand why I get a `KeyError: 'squared_error'`

in this simple code:

`KeyError: 'squared_error'`

in this simple code:

Can I extract the underlying decision-rules (or ‘decision paths’) from a trained tree in a decision tree as a textual list?

I am currently using H2O for a classification problem dataset. I am testing it out with `H2ORandomForestEstimator`

in a python 3.6 environment. I noticed the results of the predict method was giving values between 0 to 1(I am assuming this is the probability).

I apply the

decision tree classifier and the random forest classifier to my data with the following code: