naiveBayes.py

import numpy as np
import pandas as pd
from sklearn.naive_bayes import CategoricalNB

rows = int(input("Input number of rows: "))
cols = int(input("Input number of features (not including label): "))

print("input table (with y)")
X = list()
y = list()
for i in range(rows):
    inp = list(map(int, input().split()))
    X.append(inp[:-1])
    y.append(inp[-1])

X = np.array(tuple(X))
y = np.array((y))

clf = CategoricalNB()
clf.fit(X, y)

x_pred = list(map(int, input("Enter value to predict: ").split()))
#print(x_pred)
print(clf.predict([x_pred]))