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logistics_regression.py
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logistics_regression.py
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import numpy as np
import matplotlib.pyplot as plt
def loaddata(filename):
file = open(filename)
x=[]
y=[]
for line in file.readlines():
line = line.strip().split()
x.append([1,float(line[0]),float(line[1])])
y.append(float(line[-1]))
xmat = np.mat(x)
ymat = np.mat(y).T
file.close()
return xmat, ymat
def w_calc(xmat, ymat,alpha=0.001,maxIter=10001):
# W init
W = np.mat(np.random.randn(3,1))
w_save = []
# W update
for i in range(maxIter):
H = 1/(1+np.exp(-xmat*W))
dw = xmat.T*(H-ymat) # dw:(3,1)
W -= alpha * dw
return W
xmat,ymat=loaddata("lr_data.txt")
print("xmat",xmat,xmat.shape)
print("ymat",ymat,ymat.shape)
W=w_calc(xmat,ymat,0.001,10000)
print('W:',W)
w0=W[0,0]
w1=W[1,0]
w2=W[2,0]
plotx1=np.arange(1,7,0.1)
plotx2=-w0/w2-w1/w2*plotx1
plt.plot(plotx1,plotx2,c='r',label='decision boundray')
plt.scatter(xmat[:,1][ymat==0].A,xmat[:,2][ymat==0].A,marker='^',s=150,label='label=0')
plt.scatter(xmat[:,1][ymat==1].A,xmat[:,2][ymat==1].A,s=150,label='label=1')
plt.grid()
plt.legend()
plt.show()