随机森林-基础分类

def solve():
    import pandas as pd
    from sklearn.ensemble import RandomForestClassifier
    from sklearn.model_selection import train_test_split
    from sklearn.metrics import accuracy_score
    df = pd.read_csv('https://liangdaima.com/static/data/iris.csv')
    X = df.drop('species', axis=1)
    y = df['species']
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
    rf = RandomForestClassifier(n_estimators=100, random_state=42)
    rf.fit(X_train, y_train)
    print('准确率:', round(accuracy_score(y_test, rf.predict(X_test)), 4))