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‎《Python数据挖掘入门与实践》/0.数据挖掘流程简单示例10min.ipynb renamed to ‎0.数据挖掘流程简单示例10min.ipynb

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‎《Python数据挖掘入门与实践》/1.近邻算法分类.ipynb renamed to ‎1.近邻算法分类.ipynb

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‎《Python数据挖掘入门与实践》/10.用深度学习进行图象分类.ipynb renamed to ‎10.用深度学习进行图象分类.ipynb

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‎《Python数据挖掘入门与实践》/11.大数据处理.ipynb renamed to ‎11.大数据处理.ipynb

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‎《Python数据挖掘入门与实践》/2.决策树预测获胜球队.ipynb renamed to ‎2.决策树预测获胜球队.ipynb

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‎《Python数据挖掘入门与实践》/3.亲和性分析推荐电影.ipynb renamed to ‎3.亲和性分析推荐电影.ipynb

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‎《Python数据挖掘入门与实践》/4.用转换器抽取特征.ipynb renamed to ‎4.用转换器抽取特征.ipynb

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‎《Python数据挖掘入门与实践》/5.朴素贝叶斯进行社会媒体挖掘.ipynb renamed to ‎5.朴素贝叶斯进行社会媒体挖掘.ipynb

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‎《Python数据挖掘入门与实践》/6.用图挖掘找到感兴趣的人.ipynb renamed to ‎6.用图挖掘找到感兴趣的人.ipynb

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‎《Python数据挖掘入门与实践》/7.用神经网络破解验证码.ipynb renamed to ‎7.用神经网络破解验证码.ipynb

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‎《Python数据挖掘入门与实践》/8.作者归属问题.ipynb renamed to ‎8.作者归属问题.ipynb

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‎《Python数据挖掘入门与实践》/9.新闻语料分类.ipynb renamed to ‎9.新闻语料分类.ipynb

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‎《Python数据挖掘入门与实践》/BOOK_CODE/Chapter 1/.ipynb_checkpoints/ch1_affinity-checkpoint.ipynb renamed to ‎BOOK_CODE/Chapter 1/.ipynb_checkpoints/ch1_affinity-checkpoint.ipynb

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‎《Python数据挖掘入门与实践》/BOOK_CODE/Chapter 1/.ipynb_checkpoints/ch1_affinity_create-checkpoint.ipynb renamed to ‎BOOK_CODE/Chapter 1/.ipynb_checkpoints/ch1_affinity_create-checkpoint.ipynb

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" X[i][0] = 1\n",
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34-
" X[i][1] = 1\n",
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" if np.random.random() < 0.2:\n",
36-
" # Who likes cheese\n",
37-
" X[i][2] = 1\n",
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" if np.random.random() < 0.25:\n",
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" X[i][3] = 1\n",
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47-
" # Who likes milk\n",
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" X[i][1] = 1\n",
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37+
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38+
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40+
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41+
" if np.random.random() < 0.5:\n",
42+
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43+
" X[i][4] = 1\n",
44+
" else:\n",
45+
" # Not a bread winner\n",
46+
" if np.random.random() < 0.5:\n",
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" # Who likes milk\n",
48+
" X[i][1] = 1\n",
49+
" if np.random.random() < 0.2:\n",
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51+
" X[i][2] = 1\n",
52+
" if np.random.random() < 0.25:\n",
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" # Who likes apples\n",
54+
" X[i][3] = 1\n",
55+
" if np.random.random() < 0.5:\n",
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57+
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58+
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59+
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64+
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" X[i][4] = 1\n",
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" if X[i].sum() == 0:\n",
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"source": [
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"metadata": {},
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