Random forest

 from sklearn.ensemble import RandomForestClassifier

from sklearn.metrics import accuracy_score

from sklearn.model_selection import train_test_split

import pandas as pd


data = pd.read_csv("heart.csv") # Load dataset (ensure heart.csv is available)

X, y = data.iloc[:, :-1], data.iloc[:, -1] # Features and target

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

model = RandomForestClassifier(n_estimators=100, random_state=42).fit(X_train, y_train)

y_pred = model.predict(X_test)

print("Accuracy:", accuracy_score(y_test, y_pred)) # Print accuracy

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