Google Colab ModuleNotFoundError: No module named 'sklearn.externals.joblib'

Question

我的初始导入看起来像这样，这个代码块运行良好。

# Libraries to help with reading and manipulating data
import numpy as np
import pandas as pd

# Libraries to help with data visualization
import matplotlib.pyplot as plt
import seaborn as sns

sns.set()

# Removes the limit for the number of displayed columns
pd.set_option("display.max_columns", None)
# Sets the limit for the number of displayed rows
pd.set_option("display.max_rows", 200)

# to split the data into train and test
from sklearn.model_selection import train_test_split

# to build linear regression_model
from sklearn.linear_model import LinearRegression

# to check model performance
from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score

但是当我尝试执行命令时出现错误 ModuleNotFoundError: No module named 'sklearn.externals.joblib'

我尝试使用 !pip 安装所有模块和针对此错误的其他建议，但均无效。这是 google colab，所以不确定我缺少什么

from mlxtend.feature_selection import SequentialFeatureSelector as SFS

Answer 1

对于第二部分，您可以这样做来修复它，我也复制了您的其余代码，并添加了底部部分。

# Libraries to help with reading and manipulating data
import numpy as np
import pandas as pd

# Libraries to help with data visualization
import matplotlib.pyplot as plt
import seaborn as sns

sns.set()

# Removes the limit for the number of displayed columns
pd.set_option("display.max_columns", None)
# Sets the limit for the number of displayed rows
pd.set_option("display.max_rows", 200)

# to split the data into train and test
from sklearn.model_selection import train_test_split

# to build linear regression_model
from sklearn.linear_model import LinearRegression

# to check model performance
from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score

# I changed this part
!pip install mlxtend
import joblib
import sys
sys.modules['sklearn.externals.joblib'] = joblib
from mlxtend.feature_selection import SequentialFeatureSelector as SFS

对我有用。