交叉验证评估

def solve():
    from sklearn.datasets import load_iris
    from sklearn.ensemble import RandomForestClassifier
    from sklearn.model_selection import cross_val_score
    import numpy as np
    iris = load_iris()
    X = iris.data
    y = iris.target
    best_n, best_score = ____, ____
    for n in [____, ____, ____, ____]:
        model = RandomForestClassifier(____)
        scores = cross_val_score(____)
        if scores.mean() > best_score:
            best_score = scores.mean()
            best_n = n
    print(____)