naive_bayes_process.py

from sklearn.model_selection import train_test_split
from sklearn import datasets

data_x, data_y = datasets.make_classification(n_samples=10000, n_features=5, n_classes=2, random_state=123)
x_tr, x_ts, y_tr, y_ts = train_test_split(data_x, data_y, test_size=0.2, random_state=123)

nb = NaiveBayes(x_tr, y_tr)
nb.fit()
preds = nb.predict(x_ts)

print('Accuracy:', np.sum(y_ts == preds) / len(x_ts))

# '> Accuracy: 0.9145