今天老师讲了一些数学的东西,传统演算法与机器学习的演算法差异,机器学习演算法有哪些方式去回测参数,但目前提到觉得不错的就是梯度下降法,可以不断修正让AUC最高,也练习利用LinearRegression预测股价
import numpy as npimport matplotlib.pyplot as pltimport pandas as pddata = pd.read_csv('2330.csv')data.head()print(data.columns)X = data[['x1', 'x2', 'x3', 'x4', 'x5']].values.reshape(-1,5)Y = data['y'].values.reshape(-1,1)from sklearn.linear_model import LinearRegression as LRmodel = LR()model.fit(X,Y)preY = model.predict(X)data['preY'] = preYprint(data.tail(1))testX = data.iloc[-1,1:6].values.reshape(-1,5)print(testX)ans = model.predict(testX)print(ans)