构建Logistic回归模型时,AttributeError:';str';对象没有属性';decode';
问题描述
我正在尝试建立Logistic回归模型,但它显示AttributeError: 'str' object has no attribute 'decode'
。请帮我解决这个问题。此代码在Datacamp的服务器上运行良好,但在我的笔记本电脑上显示AttributeError。
import pandas as pd
df = pd.read_csv('datasets/diabetes.csv')
X = df.drop('diabetes',axis = 1)
y = df['diabetes']
# Import the necessary modules
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import classification_report, confusion_matrix
# Create training and test sets
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.4, random_state=42)
# Create the classifier: logreg
logreg = LogisticRegression()
# Fit the classifier to the training data
logreg.fit(X_train,y_train)
错误消息:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-8-c8cf98ee145a> in <module>
16
17 # Fit the classifier to the training data
---> 18 logreg.fit(X_train,y_train)
19
20 #Predict the labels of the test set: y_pred
~anaconda3envs ensorflowlibsite-packagessklearnlinear_model\_logistic.py in fit(self, X, y,
sample_weight)
1405 else:
1406 prefer = 'processes'
-> 1407 fold_coefs_ = Parallel(n_jobs=self.n_jobs, verbose=self.verbose,
1408 **_joblib_parallel_args(prefer=prefer))(
1409 path_func(X, y, pos_class=class_, Cs=[C_],
~anaconda3envs ensorflowlibsite-packagessklearnutilsoptimize.py in
_check_optimize_result(solver, result, max_iter, extra_warning_msg)
241 " https://scikit-learn.org/stable/modules/"
242 "preprocessing.html"
--> 243 ).format(solver, result.status, result.message.decode("latin1"))
244 if extra_warning_msg is not None:
245 warning_msg += "
" + extra_warning_msg
AttributeError: 'str' object has no attribute 'decode'
如有任何建议,我们将不胜感激
解决方案
这似乎是SCHKITL学习版的问题。
无论如何,在最新版本的SCRICIT-LEARN(现在是0.24.1)中,这个问题已经修复,将部分代码包含在try-Catch块中。Gigioz在此堆栈溢出question中对此进行了更详细的解释。
可能您有较旧的版本,所以我建议您使用下面的代码升级SCRICKIT-LINE库:
pip install -U scikit-learn
然后重新启动内核,检查新版本是否正确更新,并再次运行代码。
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