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import pandas as pd
import matplotlib.pyplot as plt
from sklearn import tree
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import train_test_split

heart=pd.read_csv('heart.csv')
heart.head()

x=heart.drop('target',axis=1)
y=heart['target']
x_train,x_test,y_train,y_test=train_
test_split(x,y,test_size=0.2,random_
state=0)

clf_tree=tree.DecisionTreeClassifier(max_depth=3)
clf_tree.fit(x_train,y_train)

clf_forest=RandomForestClassifier(n_estimators=1)
clf_forest.fit(x_train,y_train)

tree.plot_tree(clf_tree)
plt.show()
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