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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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