Hey Shubham,
I am a project reviewer at Udacity. This code seems to be part of one of
our projects (P1 - Boston Housing
<https://github.com/WittmannF/Machine_Learning-Boston_Housing/blob/master/boston_housing.ipynb>).
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
<http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.ShuffleSplit.html>).
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 <
tomarshubha...@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 <http://Autodidact24.github.io>*
>
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>
>
--
Fernando Marcos Wittmann
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