混淆矩阵

def solve():
    from sklearn.datasets import load_iris
    from sklearn.svm import SVC
    from sklearn.preprocessing import StandardScaler
    from sklearn.metrics import accuracy_score
    iris = load_iris()
    X = iris.data
    y = iris.target
    scaler = StandardScaler()
    X_s = scaler.fit_transform(X)
    best_acc = 0
    for kernel in ['linear', 'rbf', 'poly']:
        model = SVC(kernel=kernel, random_state=42).fit(X_s, y)
        acc = accuracy_score(y, model.predict(X_s))
        if acc > best_acc:
            best_acc = acc
    print(f'{best_acc:.4f}')