import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.naive_bayes import GaussianNB
from sklearn.metrics import accuracy_score

X = np.array([[1, 2], [2, 3], [3, 4], [4, 5], [5, 6],
              [6, 7], [7, 8], [8, 9], [9, 10], [10, 11]])
y = np.array([0, 0, 0, 0, 0, 1, 1, 1, 1, 1])

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)
model = GaussianNB()
model.fit(X_train, y_train)
y_pred = model.predict(X_test)
accuracy = accuracy_score(y_test, y_pred)
print(f"Accuracy: {accuracy * 100:.2f}%")