Weekly数据集整体逻辑回归

import pandas as pd
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score, confusion_matrix
weekly = pd.read_csv('https://liangdaima.com/static/data/statistics/Weekly.csv')
weekly['Direction'] = (weekly['Direction'] == 'Up').astype(int)
X = weekly[['Lag1', 'Lag2', 'Lag3', 'Lag4', 'Lag5', 'Volume']]
y = weekly['Direction']
model = LogisticRegression()
model.fit(X, y)
pred = model.predict(X)
print('整体准确率:', accuracy_score(y, pred))
print('混淆矩阵:')
print(confusion_matrix(y, pred))