[FIXED] Display all parameters of an estimator including defaults

Issue

I am using Watson Studio and using a markdown notebook. In the notebook, I write the code:

from sklearn.tree import DecisionTreeClassifier
Tree_Loan= DecisionTreeClassifier(criterion="entropy", max_depth = 4)
Tree_Loan

and it displays

DecisionTreeClassifier(criterion='entropy', max_depth=4)

However, it should display something in the form of (this is from a different lab I've done using Skills Network Labs):

DecisionTreeClassifier(class_weight=None, criterion='entropy', max_depth=4,
            max_features=None, max_leaf_nodes=None,
            min_impurity_decrease=0.0, min_impurity_split=None,
            min_samples_leaf=1, min_samples_split=2,
            min_weight_fraction_leaf=0.0, presort=False, random_state=None,
            splitter='best')

The best I can tell is that it is not importing the decision tree classifier. I have the same problem with svm from sklearn. Other functions in scikit-learn like train test split and k nearest neighbors work fine. A classmate says the rest of my code is correct and there is no reason for the error. What might be causing it?

Solution

It is importing the DecisionTreeClassifier, no problem there. But by default, sklearn prints only the parameters that were given to estimator with non-default values, from this function.

But if you want to see the "full" output, you can set the configuration of print_changed_only to False via sklearn._config.set_config like so:

>>> from sklearn.tree import DecisionTreeClassifier
>>> tree = DecisionTreeClassifier(criterion="entropy", max_depth=4)

>>> # only displays the changed parameters
>>> tree
DecisionTreeClassifier(criterion='entropy', max_depth=4)

>>> from sklearn._config import get_config, set_config

>>> # default setting
>>> get_config()["print_changed_only"]
True

>>> # now changing it 
>>> set_config(print_changed_only=False)

# now we get the default values, too
>>> tree

DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='entropy',
                       max_depth=4, max_features=None, max_leaf_nodes=None,
                       min_impurity_decrease=0.0, min_impurity_split=None,
                       min_samples_leaf=1, min_samples_split=2,
                       min_weight_fraction_leaf=0.0, presort='deprecated',
                       random_state=None, splitter='best')

Answered By - Mustafa Aydın