testRegression.py 文件源码

def testLocallyWeightedRegression():
    datasArr, valuessArr = loadDataSet('datasets/ex0.txt')
    m = np.shape(datasArr)[0]
    predictValues = np.zeros(m)
    for i in range(0, m):
        predictValues[i] = \
            locallyWeightedRegression(datasArr[i], datasArr, valuessArr, 0.01)

    # ??????
    xMat = np.matrix(datasArr)
    valueMat = np.matrix(valuessArr)
    plt.figure(figsize=(10, 10), facecolor="white")
    plt.subplot(111)
    plt.scatter(xMat[:, 1].flatten().A[0], valueMat.T.flatten().A[0])
    # ???????
    # ??????????
    sortedIndexs = xMat[:, 1].argsort(0)
    print "sortedIndexs:"
    print sortedIndexs
    sortedMat = xMat[sortedIndexs.flatten().A[0]]
    plt.plot(sortedMat[:, 1], predictValues[sortedIndexs], c='red', linewidth=2)
    plt.show()
    # ?????????????
    correlationCoefficients = np.corrcoef(predictValues, valueMat)
    print "?????", correlationCoefficients