Classification using NaiveBayse Algorithm using Python

#Import Library of Gaussian Naive Bayes model
from sklearn.naive_bayes import GaussianNB
import numpy as np

import pandas as pd

#assigning predictor and target variables
dataF = pd.DataFrame()

dataF["x1"] = np.random.random_sample((5,)) + 1

dataF["x2"] = np.random.random_sample((5,)) + 2 

dataL = pd.DataFrame()

dataL = np.array([3, 3, 4, 3, 4])

#Create a Gaussian Classifier
model = GaussianNB()

# Train the model using the training sets 
model.fit(dataF, dataL)

#Predict Output 
predicted= model.predict([[1,2],[3,4]])
print(predicted)

Output: ([3,4])

-Thank you