''' Created on 2014年4月2日 @author: EASON ''' import logistic dataArr, labelMat = logistic.loadDataSet() weights = logistic.gradAscent(dataArr, labelMat) print(weights)
''' Created on 2014年4月2日 @author: EASON ''' import logistic dataArr,labelMat = logistic.loadDataSet() weights = logistic.gradAscent(dataArr,labelMat) print(weights)
ycord1 = []
xcord2 = []
ycord2 = []
for i in range(m):
if int(labelMat[i]) == 1:
xcord1.append(dataArr[i, 1])
ycord1.append(dataArr[i, 2])
else:
xcord2.append(dataArr[i, 1])
ycord2.append(dataArr[i, 2])
fig = plt.figure()
ax = fig.add_subplot(111)
ax.scatter(xcord1, ycord1, s=30, c='red', marker='s')
ax.scatter(xcord2, ycord2, s=30, c='green')
x = np.arange(-4, 4)
y = (-weights[0] - weights[1] * x) / weights[2]
plt.plot(x, y)
plt.xlabel('X1')
plt.ylabel('X2')
plt.show()
dataMat, labelMat = loadDateSet()
weights = gradAscent(dataMat, labelMat)
weights_new = stocGradAscent(dataMat, labelMat)
weights_new1 = stocGradAscent1(np.array(dataMat), labelMat)
print type(weights)
print weights.getA()
print type(weights.getA())
plotBestFit(weights_new1)
import logistic dataArr, labelMat = logistic.loadDataSet() print(dataArr, labelMat) logistic.gradAscent(dataArr, labelMat) print(logistic.gradAscent(dataArr, labelMat))