Python双色球训练模型

import pandas as pd
import numpy as np
from sklearn.neural_network import MLPRegressor
# 读取历史数据
data = pd.read_csv('history_data.csv')
# 处理数据，提取特征
features = []
for i in range(1, 34):
    features.append('r' + str(i))
for i in range(1, 17):
    features.append('b' + str(i))
X = np.array(data[features])
y = np.array(data['result'])
    # 构建神经网络模型
model = MLPRegressor(hidden_layer_sizes=(100, 50), max_iter=1000, alpha=0.0001, solver='lbfgs', verbose=10, random_state=1, tol=0.0001)
    # 训练模型
model.fit(X, y)
# 预测下一期开奖号码
next_data = pd.read_csv('next_data.csv')
next_X = np.array(next_data[features])
next_result = model.predict(next_X)
print('下一期开奖号码预测结果：', next_result)