''' 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))