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machine_learning/random_forest_classifier.py.broken.txt
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Victor Rodrigues da Silva
Add autoclave cipher (#8029)
19 дек 2022, 01:26
Не верифицирован
19 дек 2022, 01:26
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# Random Forest Classifier Example from matplotlib import pyplot as plt from sklearn.datasets import load_iris from sklearn.ensemble import RandomForestClassifier from sklearn.metrics import plot_confusion_matrix from sklearn.model_selection import train_test_split def main(): """ Random Forest Classifier Example using sklearn function. Iris type dataset is used to demonstrate algorithm. """ # Load Iris dataset iris = load_iris() # Split dataset into train and test data x = iris["data"] # features y = iris["target"] x_train, x_test, y_train, y_test = train_test_split( x, y, test_size=0.3, random_state=1 ) # Random Forest Classifier rand_for = RandomForestClassifier(random_state=42, n_estimators=100) rand_for.fit(x_train, y_train) # Display Confusion Matrix of Classifier plot_confusion_matrix( rand_for, x_test, y_test, display_labels=iris["target_names"], cmap="Blues", normalize="true", ) plt.title("Normalized Confusion Matrix - IRIS Dataset") plt.show() if __name__ == "__main__": main()