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- from sklearn.naive_bayes import GaussianNB
- from sklearn.model_selection import cross_val_score, train_test_split
- from datasets import Datasets
- def main():
- train_data, vaild_data, test_data = Datasets.load_mnist()
- x_train, y_train = train_data
- x_test, y_test = test_data
- gnb = GaussianNB()
- gnb.fit(x_train, y_train)
- print(gnb.score(x_test, y_test)) # 0.5544
- scores = cross_val_score(gnb, x_test, y_test, cv=3, scoring="accuracy")
- print(scores.mean()) # 0.5752038611179655
- if __name__ == "__main__":
- main()
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