human
I am working on the file "HandsOnML/03Classification.ipynb".
The first task is:
As we can see accuract is above 90% in all cases, it seems weird, let's check the base estimate
Can you write Python code for it?
assistant
#Here is the Python code you requested.

from sklearn.base import BaseEstimator

class Never5Classifier(BaseEstimator):
    def fit(self, X, y=None):
        pass
    def predict(self, X):
        return np.zeros((len(X), 1), dtype=bool)

never_5_clf = Never5Classifier()
cross_val_score(never_5_clf, X_train, y_train_5, cv=3, scoring="accuracy")