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from sklearn import datasets
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import LeaveOneOut, cross_val_score
​
X, y = datasets.load_iris(return_X_y=True)
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clf = DecisionTreeClassifier(random_state=42)
​
loo = LeaveOneOut()
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scores = cross_val_score(clf, X, y, cv = loo)
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print("Cross Validation Scores: ", scores)
print("Average CV Score: ", scores.mean())
print("Number of CV Scores used in Average: ", len(scores)) 
​
Cross Validation Scores:  [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.
 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.
 1. 1. 1. 1. 1. 1. 1. 1. 1. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 0. 1.
 1. 1. 1. 1. 1. 0. 1. 1. 1. 1. 1. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.
 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 0.
 1. 1. 1. 1. 1. 1. 1. 1. 1. 0. 1. 1. 1. 0. 1. 1. 1. 1. 0. 1. 1. 1. 1. 1.
 1. 1. 1. 1. 1. 1.]
Average CV Score:  0.94
Number of CV Scores used in Average:  150