Hey Shubham, 

I am a project reviewer at Udacity. This code seems to be part of one of our projects (P1 - Boston Housing). I think that you have updated the old module sklearn.cross_validation to the module sklearn.model_detection, is that correct? If yes, then you should also update the parameters in ShuffleSplit to match with this new version (check the docs). Try to update ShuffleSplit to the following line of code:

    cv_sets = ShuffleSplit(n_splits=10, test_size=0.2, random_state=0)

I hope that helps! Feel free to send me a PM. 

On Tue, Mar 7, 2017 at 10:24 AM, Shubham Singh Tomar <tomarshubham24@gmail.com> wrote:

Hi,

I'm trying to use GridSearchCV to tune the parameters for DecisionTreeRegressor. I'm using sklearn 0.18.1

I'm getting the following error:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-36-192f7c286a58> in <module>()
      1 # Fit the training data to the model using grid search
----> 2 reg = fit_model(X_train, y_train)
      3 
      4 # Produce the value for 'max_depth'
      5 print "Parameter 'max_depth' is {} for the optimal model.".format(reg.get_params()['max_depth'])

<ipython-input-35-500141c331d9> in fit_model(X, y)
     11 
     12     # Create cross-validation sets from the training data
---> 13     cv_sets = ShuffleSplit(X.shape[0], n_splits = 10, test_size = 0.20, random_state = 0)
     14 
     15     # TODO: Create a decision tree regressor object

TypeError: __init__() got multiple values for keyword argument 'n_splits'

--

Thanks,

Shubham Singh Tomar

Autodidact24.github.io

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--

Fernando Marcos Wittmann

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