决策树分类可视化

def solve():
    import pandas as pd
    import matplotlib.pyplot as plt
    from sklearn.tree import DecisionTreeClassifier, plot_tree
    from sklearn.model_selection import train_test_split
    df = pd.read_csv("https://data.zuihe.com/iris.csv")
    X = df.drop("species", axis=1); y = df["species"]
    X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)
    tree = DecisionTreeClassifier(max_depth=3, random_state=42).fit(X_train, y_train)
    plt.figure(figsize=(12, 8))
    plot_tree(tree, feature_names=X.columns, class_names=tree.classes_, filled=True)
    plt.show()
    print(f"{tree.score(X_test, y_test):.2f}")