Python - Classification - Decission Tree (DT)


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.tree import DecisionTreeRegressor

url = ''
vlog123 = pd.read_csv(url)

X = vlog123[['Usia','Gaji (juta)']]
y = vlog123['Skor Belanja (1-100)']

d3 = DecisionTreeRegressor(), y)

usia = input("Usia (thn): ")
usia = int(usia)
gaji = input("Gaji (juta): ")
gaji = int(gaji)
data = [usia,gaji]
print("Prediksi Skor Belanja (1-100): ", d3.predict([data]))

plt.scatter(vlog123[['Gaji (juta)']],y, color='green')
plt.scatter(gaji,d3.predict([data]), color='red')

I wrapped the scenario in a Youtube video below.

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