标签：imp cycle axis stat sklearn sum ram bic index
由于一些模块的变迁，导致复现《python数据科学手册》代码（尤其第5章-机器学习）时，经常报错。
以下是我个人的一些校证。
如果诸位在学习《python数据科学手册》的过程中，遇到什么疑难，欢迎留言。
1. scikit-learn.cross_validation 模块变迁
自 `scikit-learn 0.20 `版起，已经用`model_selection`模块代替`cross_validation`模块。因此，复现代码时，`from sklearn.cross_validation import xxx` 时，会报出`ModuleNotFoundError: No module named ‘sklearn.cross_validation‘`的错误。P307:
In[15]:from sklearn.cross_validation import train_test_split # Error In[15]:from sklearn.model_selection import train_test_split # Amend In[20]: from sklearn.mixture import GMM # Error from sklearn.mixture import GaussianMixture # Amend In[5]: from sklearn.cross_validation import train_test_split # Error In[5]: from sklearn.model_selection import train_test_split # Amend
# 用 model_selection 替换 cross_validation In[7]: from sklearn.cross_validation import cross_val_scroe # Error In[7]: from sklearn.model_selection import cross_val_scroe # Amend
In[8]: from sklearn.cross_validation import cross_val_scroe # Error scores = cross_val_score(model, X, y, cv=LeaveOneOut(len(X)) # Error In[8]: from sklearn.model_selection import cross_val_scroe # Amend scores = cross_val_score(model, X, y, cv=LeaveOneOut() # Amend，去掉 len(X)
2. scikit-learn.learning_curve 模块变迁
自 `scikit-learn 0.20 `版起，已经用`model_selection`模块代替`learning_curve`模块。因此，复现代码时，`from sklearn.learning_curve import xxx` 时，会报出`ModuleNotFoundError: No module named ‘sklearn.learning_curve‘`的错误。
P321: In[13]: from sklearn.learning_curve import validation_curve # Error from sklearn.model_selection import validation_curve # Amend
P325: In[17]: from sklearn.learning_curve import learning_curve # Error from sklearn.model_selection import learning_curve # Amend
3. scikit-learn.grid_search 模块变迁
自 `scikit-learn 0.20 `版起，已经用`model_selection`模块代替`grid_search`模块。因此，复现代码时，`from sklearn.grid_search import xxx` 时，会报出`ModuleNotFoundError: No module named ‘sklearn.grid_search‘`的错误。
P326 In[18]:from sklearn.grid_search import GridSearchCV # Error In[18]:from sklearn.model_selection import GridSearchCV # Amend In[21]: plt.plot(X_test.ravel(), y_test, hold=True); # Error In[21]: plt.plot(X_test.ravel(), y_test); # Amend, 去掉 hold=True
4. 其他错误
P248: In[3]: ax = plt.axes(axisbg=‘#E6E6E6‘) # Error ax = plt.axes(facecolor=‘#E6E6E6‘) # Amend, axisbg -> facecolor P275: In[6]: plt.hist(data[col], normed=True, alpha=0.5) # Error plt.hist(data[col], density=True, alpha=0.5) # Amend, normed -> density P248: In[3]: ax = plt.axes(axisbg=‘#E6E6E6‘) # Error ax = plt.axes(facecolor=‘#E6E6E6‘) # Amend, axisbg -> facecolor P275: In[6]: plt.hist(data[col], normed=True, alpha=0.5) # Error plt.hist(data[col], density=True, alpha=0.5) # Amend, normed -> density P279: In[13]: sns.pairplot(iris, hue=‘species‘, size=2.5) # Error sns.pairplot(iris, hue=‘species‘, height=2.5) # Amend, size -> height P301: In[2]: sns.parirplot(iris, hue=‘species‘, size=1.5); # Error sns.parirplot(iris, hue=‘species‘, height=1.5); # Amend, size 改为 height P349: In[14]: weather = pd.read_csv(‘599021.csv‘, index_col=‘DATE‘, parse_dates=True) # Error weather = pd.read_csv(‘599021.csv‘, index_col=‘DATE‘, parse_dates=True) # Amend, 599021.csv -> BicycleWeather.csv In[15]: daily = counts.resample(‘d‘, how=‘sum‘) # Error In[15]: daily = counts.resample(‘d‘).sum() # Amend P361: In[14]: clf = SVC(kernel=‘rbf‘, C=1E6) # Error In[14]: clf = SVC(kernel=‘rbf‘, C=1E6, gamma=‘auto‘) # Amend, add gamma=‘auto‘ P363 In[20]: from sklearn.decomposition import RandomizedPCA # Error pac = RandomizedPCA(n_components=150, whiten=True, random_state=42) # Error from sklearn.decomposition import PCA # Amend, RandomizedPCA -> PCA pac = PCA(n_components=150, whiten=True, random_state=42) # Amend, RandomizedPCA -> PCA P364: In[21]: from sklearn.cross_validation import train_test_split # Error In[21]: from sklearn.model_selection import train_test_split # Amend In[22]: from sklearn.grid_search import GridSearchCV # Error grid = GridSearchCV(model, param_grid) # Error In[22]: from sklearn.model_selection import GridSearchCV # Amend grid = GridSearchCV(model, param_grid, cv=3) # Amend, add cv=3 P279: In[13]: sns.pairplot(iris, hue=‘species‘, size=2.5) # Error sns.pairplot(iris, hue=‘species‘, height=2.5) # Amend, size -> height P301: In[2]: sns.parirplot(iris, hue=‘species‘, size=1.5); # Error sns.parirplot(iris, hue=‘species‘, height=1.5); # Amend, size 改为 height P349: In[14]: weather = pd.read_csv(‘599021.csv‘, index_col=‘DATE‘, parse_dates=True) # Error weather = pd.read_csv(‘599021.csv‘, index_col=‘DATE‘, parse_dates=True) # Amend, 599021.csv -> BicycleWeather.csv In[15]: daily = counts.resample(‘d‘, how=‘sum‘) # Error In[15]: daily = counts.resample(‘d‘).sum() # Amend P361: In[14]: clf = SVC(kernel=‘rbf‘, C=1E6) # Error In[14]: clf = SVC(kernel=‘rbf‘, C=1E6, gamma=‘auto‘) # Amend, add gamma=‘auto‘ P248: In[3]: ax = plt.axes(axisbg=‘#E6E6E6‘) # Error ax = plt.axes(facecolor=‘#E6E6E6‘) # Amend, axisbg -> facecolor P275: In[6]: plt.hist(data[col], normed=True, alpha=0.5) # Error plt.hist(data[col], density=True, alpha=0.5) # Amend, normed -> density P279: In[13]: sns.pairplot(iris, hue=‘species‘, size=2.5) # Error sns.pairplot(iris, hue=‘species‘, height=2.5) # Amend, size -> height P301: In[2]: sns.parirplot(iris, hue=‘species‘, size=1.5); # Error sns.parirplot(iris, hue=‘species‘, height=1.5); # Amend, size 改为 height P349: In[14]: weather = pd.read_csv(‘599021.csv‘, index_col=‘DATE‘, parse_dates=True) # Error weather = pd.read_csv(‘599021.csv‘, index_col=‘DATE‘, parse_dates=True) # Amend, 599021.csv -> BicycleWeather.csv In[15]: daily = counts.resample(‘d‘, how=‘sum‘) # Error In[15]: daily = counts.resample(‘d‘).sum() # Amend P361: In[14]: clf = SVC(kernel=‘rbf‘, C=1E6) # Error In[14]: clf = SVC(kernel=‘rbf‘, C=1E6, gamma=‘auto‘) # Amend, add gamma=‘auto‘ P363: In[20]: from sklearn.decomposition import RandomizedPCA # Error pac = RandomizedPCA(n_components=150, whiten=True, random_state=42) # Error from sklearn.decomposition import PCA # Amend, RandomizedPCA -> PCA pac = PCA(n_components=150, whiten=True, random_state=42) # Amend, RandomizedPCA -> PCA P364: In[21]: from sklearn.cross_validation import train_test_split # Error In[21]: from sklearn.model_selection import train_test_split # Amend In[22]: from sklearn.grid_search import GridSearchCV # Error grid = GridSearchCV(model, param_grid) # Error In[22]: from sklearn.model_selection import GridSearchCV # Amend grid = GridSearchCV(model, param_grid, cv=3) # Amend, add cv=3 P363 In[20]: from sklearn.decomposition import RandomizedPCA # Error pac = RandomizedPCA(n_components=150, whiten=True, random_state=42) # Error from sklearn.decomposition import PCA # Amend, RandomizedPCA -> PCA pac = PCA(n_components=150, whiten=True, random_state=42) # Amend, RandomizedPCA -> PCA P364: In[21]: from sklearn.cross_validation import train_test_split # Error In[21]: from sklearn.model_selection import train_test_split # Amend In[22]: from sklearn.grid_search import GridSearchCV # Error grid = GridSearchCV(model, param_grid) # Error In[22]: from sklearn.model_selection import GridSearchCV # Amend grid = GridSearchCV(model, param_grid, cv=3) # Amend, add cv=3
标签：imp cycle axis stat sklearn sum ram bic index
原文地址：https://www.cnblogs.com/xiangsui/p/11665914.html
