酶活性检测机器学习源代码（欠拟合、过拟合）

import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression
from sklearn.metrics import r2_score
from sklearn.preprocessing import PolynomialFeatures

data_train = pd.read_csv('T-R-train.csv')  # 数据预先分离
data_test = pd.read_csv('T-R-test.csv')
# print(data_train)

x_train = data_train.loc[:, 'T']
y_train = data_train.loc[:, 'rate']
x_test = data_test.loc[:, 'T']
y_test = data_test.loc[:, 'rate']

x_train = np.array(x_train).reshape(-1,1)

# fig1 = plt.figure()
# plt.scatter(x_train, y_train)
# plt.title('raw data')
# plt.xlabel('temperature')
# plt.ylabel('rate')
# plt.show()

x_train = np.array(x_train).reshape(-1, 1)
x_test = np.array(x_test).reshape(-1, 1)

# 线性回归模型
lr1 = LinearRegression()
lr1.fit(x_train, y_train)
y_train_predict = lr1.predict(x_train)
y_test_predi