如何使用scikitlearn保存一个热门的编码模型并预测新的未编码数据？

from sklearn import preprocessing
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
import joblib

encoder = preprocessing.LabelEncoder()
X_encoded = encoder.fit_transform(X)

X_train, X_test, y_train, y_test = train_test_split(X_encoded, y, test_size=0.2, random_state=42)

model = LogisticRegression()
model.fit(X_train, y_train)

joblib.dump(model, 'model.pkl')

loaded_model = joblib.load('model.pkl')
new_data = [1, 2, 3]  # 未编码的新数据
new_data_encoded = encoder.transform(new_data)
prediction = loaded_model.predict([new_data_encoded])