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@amankharwal
Created Jul 10, 2021
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import numpy
import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeClassifier
data = pd.read_csv("https://raw.githubusercontent.com/amankharwal/Website-data/master/social.csv")
x = np.array(data[["Age", "EstimatedSalary"]])
y = np.array(data[["Purchased"]])
xtrain, xtest, ytrain, ytest = train_test_split(x, y, test_size=0.10, random_state=42)
model = DecisionTreeClassifier()
model.fit(xtrain, ytrain)
predictions = model.predict(xtest)
# Calculation of F-beta Score
from sklearn.metrics import fbeta_score
print(fbeta_score(ytest, predictions, beta=1))
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