3.3 編程實現對率回歸，並給出西瓜數據集3.0α上的結果。
本題我就調用了sklearn的邏輯回歸庫來測試。
#!/usr/bin/python # -*- coding:utf-8 -*- from sklearn import linear_model,datasets import numpy as np from matplotlib import pyplot as plt file1 = open('c:\quant\watermelon.csv','r') data = [line.strip('\n').split(',') for line in file1] X = [[float(raw[-3]), float(raw[-2])] for raw in data[1:]] Y = [1 if raw[-1]=='\xca\xc7' else 0 for raw in data[1:]] X = np.array(X) # import some data to play with h = .002 # step size in the mesh logreg = linear_model.LogisticRegression(C=1e5) # we create an instance of Neighbours Classifier and fit the data. logreg.fit(X, Y) # Plot the decision boundary. For that, we will assign a color to each # point in the mesh [x_min, m_max]x[y_min, y_max]. x_min, x_max = X[:, 0].min() - .5, X[:, 0].max() + .5 y_min, y_max = X[:, 1].min() - .5, X[:, 1].max() + .5 xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h)) test = np.c_[xx.ravel(), yy.ravel()] #print test Z = logreg.predict(test) #print Z #np.c_() 連接多個數組為一個數組 # Put the result into a color plot Z = Z.reshape(xx.shape) #print Z #plt.figure(1, figsize=(4, 3)) plt.pcolormesh(xx, yy, Z, cmap=plt.cm.Paired) # Plot also the training points plt.scatter(X[:, 0], X[:, 1], c=Y, edgecolors='k', cmap=plt.cm.Paired) plt.xlabel('Density') plt.ylabel('Sugar rate') plt.xlim(xx.min(), xx.max()) plt.ylim(yy.min(), yy.max()) plt.xticks(()) plt.yticks(()) plt.show()
結果如下：
西瓜數據集如下：
編號,色澤,根蒂,敲聲,紋理,臍部,觸感,密度,含糖率,好瓜
1,青綠,蜷縮,濁響,清晰,凹陷,硬滑,0.697,0.46,是
2,烏黑,蜷縮,沉悶,清晰,凹陷,硬滑,0.774,0.376,是
3,烏黑,蜷縮,濁響,清晰,凹陷,硬滑,0.634,0.264,是
4,青綠,蜷縮,沉悶,清晰,凹陷,硬滑,0.608,0.318,是
5,淺白,蜷縮,濁響,清晰,凹陷,硬滑,0.556,0.215,是
6,青綠,稍蜷,濁響,清晰,稍凹,軟粘,0.403,0.237,是
7,烏黑,稍蜷,濁響,稍糊,稍凹,軟粘,0.481,0.149,是
8,烏黑,稍蜷,濁響,清晰,稍凹,硬滑,0.437,0.211,是
9,烏黑,稍蜷,沉悶,稍糊,稍凹,硬滑,0.666,0.091,否
10,青綠,硬挺,清脆,清晰,平坦,軟粘,0.243,0.267,否
11,淺白,硬挺,清脆,模糊,平坦,硬滑,0.245,0.057,否
12,淺白,蜷縮,濁響,模糊,平坦,軟粘,0.343,0.099,否
13,青綠,稍蜷,濁響,稍糊,凹陷,硬滑,0.639,0.161,否
14,淺白,稍蜷,沉悶,稍糊,凹陷,硬滑,0.657,0.198,否
15,烏黑,稍蜷,濁響,清晰,稍凹,軟粘,0.36,0.37,否
16,淺白,蜷縮,濁響,模糊,平坦,硬滑,0.593,0.042,否
17,青綠,蜷縮,沉悶,稍糊,稍凹,硬滑,0.719,0.103,否