Python - Classification - Naive Bayes (NB)


Questionnaire data from mall visitors contains sex, age, salary & shopping score (200 rows)


How to predict the probability of shopping score from given age & salary

Library used:

  • Pandas
  • Matplotlib
  • Scikit



import pandas as pd
import matplotlib.pyplot as plt
from sklearn.naive_bayes import GaussianNB

url = ''
vlog125 = pd.read_csv(url)

X = vlog125[['Usia','Gaji (juta)']]
y = vlog125['Skor Belanja (1-100)']

nb = GaussianNB(),y)

usia = input("Usia (thn): ")
usia = int(usia)
gaji = input("Gaji (juta): ")
gaji = int(gaji)
data = [usia,gaji]
print("Prediksi Skor Belanja (1-100): ", nb.predict([data]))

plt.scatter(vlog122[['Gaji (juta)']],y, color='green')
plt.scatter(gaji,nb.predict([data]), color='red')

I wrapped the scenario in a Youtube video below.

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