[scikit-learn] Random forest fitting very well

[muhammad waseem]

Hi All,
I am trying to use random forests for a regression problem, with 10 input
variables and one output variable. I am getting very good fit even with
default parameters and low n_estimators. Even with n_estimator = 10, I get
R^2 value of 0.95 on testing dataset (MSE=23) and a value of 0.99 for
the training set. I was wondering, if this is common with random forest or
I am missing something, Could you please share your experience? The total
number of sample (training +testing) are equal to 10971.
Also, what are the most important parameters (max_depth, bootstrap,
max_leaf_nodes etc.) that I need to play with to tune my model even
further? Lastly, is there is a way I can visualise a single tree of my
forest (just for demonstration purposes)?
Please see a figure below to demonstrate how well it is fitting with
default values.



[image: Inline image 1]
Thanks
Kindest Regards
Waseem
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