如何用Python编写随机森林算法？

import numpy as npimport pandas as pdfrom sklearn.ensemble import RandomForestClassifierfrom sklearn.model_selection import train_test_splitfrom sklearn.metrics import accuracy_score

data = pd.read_csv("iris.csv")

# 将特征和标签分开X = data.drop('species', axis=1)y = data['species']# 将分类变量转换成数值变量y = pd.factorize(y)[0]

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)

y_pred = rf.predict(X_test)accuracy = accuracy_score(y_test, y_pred)print("Accuracy:", accuracy)