ValueError: 输入包含 NaN、无穷大或对于 dtype('float64') 来说太大的值试衣错误机器学习

如何解决ValueError: 输入包含 NaN、无穷大或对于 dtype('float64') 来说太大的值试衣错误机器学习

这是我的代码：

    $ pytest -rP
    =================================== PASSES ====================================
_____________________ test_entrypointFunction[yesterday] ______________________
---------------------------- Captured stdout call -----------------------------

uut.entry_point(yesterday)-->
[1]entry_point(yesterday)-->someFunction(yesterday,1)-->amend_someApiCall_yesterday(1)
[2]entry_point(yesterday)-->someFunction2(yesterday,2)-->amend_someApiCall_yesterday(2)
_______________________ test_entrypointFunction[today] ________________________
---------------------------- Captured stdout call -----------------------------

uut.entry_point(today)-->
[1]entry_point(today)-->someFunction(today,1)-->amend_someApiCall_today(1)
[2]entry_point(today)-->someFunction2(today,2)-->amend_someApiCall_today(2)
_______________________ test_entrypointFunction[later] ________________________
---------------------------- Captured stdout call -----------------------------

uut.entry_point(later)-->
[1]entry_point(later)-->someFunction(later,1)-->amend_someApiCall_later(1)-->someSloowApiCall(11)-->I'm mocked! I'm not slow,random or hard to test
[2]entry_point(later)-->someFunction2(later,2)-->amend_someApiCall_later2(2)-->someSloowApiCall2(12)-->I'm mocked! I'm not slow,random or hard to test
______________________ test_entrypointFunction[tomorrow] ______________________
---------------------------- Captured stdout call -----------------------------

uut.entry_point(tomorrow)-->
[1]entry_point(tomorrow)-->someFunction(tomorrow,1)-->lambda(1)
[2]entry_point(tomorrow)-->someFunction2(tomorrow,2)-->lambda2(2)
______________________ test_entrypointFunction[whenever] ______________________
---------------------------- Captured stdout call -----------------------------

uut.entry_point(whenever)-->
[1]entry_point(whenever)-->someFunction(whenever,1)-->someSloowApiCall(1)-->I'm not mocked! I'm slow,random and hard to test
[2]entry_point(whenever)-->someFunction2(whenever,2)-->someSloowApiCall2(2)-->I'm not mocked! I'm slow,random and hard to test
============================== 5 passed in 0.07s ==============================

这是我的错误：

#Naive Bayes
from sklearn.naive_bayes import GaussianNB
clf = GaussianNB()
clf.fit(X_train,y_train)
prediction = clf.predict(X_test)
scores = cross_val_score(clf,X,y,cv=5)
print(accuracy_score(prediction,y_test))

我正在尝试使用朴素贝叶斯方法来教机器，但我不断收到此错误。

解决方法

看起来您的数据具有 NaN 值。放下它们。使用此代码。

X_train = X_train.dropna()
#Naive Bayes
from sklearn.naive_bayes import GaussianNB

此代码将删除包含 NaN 值的行。如果您想填充 NaN 而不是删除它们，您可以使用 .fillna(np.mean(column_name)) 用其列的平均值填充这些 NaN。