【发布时间】:2015-04-28 09:51:02
【问题描述】:
我正在尝试使用 fmin 进行逻辑回归,但由于数组的不同形状而出现错误。这是代码。
import numpy as np
import scipy.optimize as sp
data= #an array of dim (188,3)
X=data[:,0:2]
y=data[:,2]
m,n=np.shape(X)
y=y.reshape(m,1)
x=np.c_[np.ones((m,1)),X]
theta=np.zeros((n+1,1))
def hypo(x,theta):
return np.dot(x,theta)
def sigmoid(z):
return 1/(1+np.exp(-z))
def gradient(x,y,theta):#calculating Gradient
m=np.shape(x)[0]
t=hypo(x,theta)
hx=sigmoid(t)
J=-(np.dot(np.transpose(np.log(hx)),y)+np.dot(np.transpose(np.log(1-hx)),(1-y)))/m
grad=np.dot(np.transpose(x),(hx-y))/m
J= J.flatten()
grad=grad.flatten()
return J,grad
def costFunc(x,y,theta):
return gradient(x,y,theta)[0]
def Grad():
return gradient(x,y,theta)[1]
sp.fmin( costFunc, x0=theta, args=(x, y), maxiter=500, full_output=True)
显示的错误
File "<ipython-input-3-31a0d7ca38c8>", line 35, in costFunc
return gradient(x,y,theta)[0]
File "<ipython-input-3-31a0d7ca38c8>", line 25, in gradient
t=hypo(x,theta)
File "<ipython-input-3-31a0d7ca38c8>", line 16, in hypo
return np.dot(x,theta)
ValueError: shapes (3,) and (118,1) not aligned: 3 (dim 0) != 118 (dim 0)
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