Checking for models' accuracy and plot them

checking-for-accuracies.py

model_accuracies = []

for i in range(1000):
    (training_inputs,
     testing_inputs,
     training_classes,
     testing_classes) = train_test_split(all_inputs, all_classes, train_size=0.7)
    
    decision_tree_classifier = DecisionTreeClassifier()
    decision_tree_classifier.fit(training_inputs, training_classes)
    classifier_accuracy = decision_tree_classifier.score(testing_inputs, testing_classes)
    model_accuracies.append(classifier_accuracy)
    
sns.distplot(model_accuracies)