November 2019
Intermediate to advanced
320 pages
13h 35m
French
Content preview from Machine Learning avec Scikit-Learn
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Chapitre 3. Classification
Pouvez-vous deviner le taux d’exactitude de ce modèle? Voyons voir:
>>> never_5_clf = Never5Classifier()
>>> cross_val_score(never_5_clf, X_train, y_train_5, cv=3, scoring="accuracy")
array([0.91125, 0.90855, 0.90915])
Vous avez bien vu, il est supérieur à 90 %! C’est simplement parce que les 5
ne représentent qu’environ 10% des images, et donc si vous décidez à chaque fois
qu’une image n’est pas un 5, vous aurez raison dans à peu près 90% des cas. C’est
mieux que Nostradamus!
Ceci démontre pourquoi l’exactitude n’est pas en général la mesure de performance
de prédilection pour les classicateurs, surtout lorsqu’on ...
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