逻辑回归推导

#逻辑回归
import pandas as pda
 
fname = 'F://anacondadaima//shujuchuli//suanfa//luqu.csv'
dataf = pda.read_csv(fname)
x = dataf.iloc[:,1:4].as_matrix() #iloc[]切片，转为数组
y = dataf.iloc[:,0:1].as_matrix()
 
from sklearn.linear_model import LogisticRegression as LR     #导入回归模型
from sklearn.linear_model import RandomizedLogisticRegression as RLR #导入随机模型
 
r1 = RLR()      #建立随机逻辑模型（用于筛选）
r1.fit(x,y)       #将x，y导入模型
r1.get_support(indices=True)  #获取有效特征（特征筛选）降维
#print(dataf.columns[r1.get_support(indices=True)])
t = dataf[dataf.columns[r1.get_support(indices=True)]].as_matrix()
 
r2 = LR()    #建立逻辑模型
r2.fit(t,y)
print('训练结束')
print('模型正确率为：'+str(r2.score(x,y)))