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Machine Learning with scikit-learn - vluzzy - 01-02-2024
from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score
# Load the Iris dataset
iris = datasets.load_iris()
X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size=0.2)
# Train a Random Forest classifier
clf = RandomForestClassifier(n_estimators=100)
clf.fit(X_train, y_train)
# Make predictions and calculate accuracy
predictions = clf.predict(X_test)
accuracy = accuracy_score(y_test, predictions)
print("Accuracy:", accuracy)