Scikit学习 - ValueError：操作数无法一起播放

我试图在数据集上应用Gaussian Naive Bayes模型来预测疾病。当我使用训练数据进行预测时，它运行正常，但是当我试图预测使用测试数据时它正在给出ValueError。Scikit学习 - ValueError：操作数无法一起播放

runfile('D:/ROFI/ML/Heart Disease/prediction.py', wdir='D:/ROFI/ML/Heart Disease') Traceback (most recent call last):

File "", line 1, in runfile('D:/ROFI/ML/Heart Disease/prediction.py', wdir='D:/ROFI/ML/Heart Disease')

File "C:\Users\User\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 866, in runfile execfile(filename, namespace)

File "C:\Users\User\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 102, in execfile exec(compile(f.read(), filename, 'exec'), namespace)

File "D:/ROFI/ML/Heart Disease/prediction.py", line 85, in predict(x_train, y_train, x_test, y_test)

File "D:/ROFI/ML/Heart Disease/prediction.py", line 73, in predict predicted_data = model.predict(x_test)

File "C:\Users\User\Anaconda3\lib\site-packages\sklearn\naive_bayes.py", line 65, in predict jll = self._joint_log_likelihood(X)

File "C:\Users\User\Anaconda3\lib\site-packages\sklearn\naive_bayes.py", line 429, in _joint_log_likelihood n_ij -= 0.5 * np.sum(((X - self.theta_[i, :]) ** 2) /

ValueError: operands could not be broadcast together with shapes (294,14) (15,)

这里有什么问题？

import pandas 
from sklearn import metrics 
from sklearn.preprocessing import Imputer 
from sklearn.naive_bayes import GaussianNB  

def load_data(feature_columns, predicted_column): 

    train_data_frame = pandas.read_excel("training_data.xlsx") 
    test_data_frame = pandas.read_excel("testing_data.xlsx") 
    data_frame = pandas.read_excel("data_set.xlsx") 

    x_train = train_data_frame[feature_columns].values 
    y_train = train_data_frame[predicted_column].values 

    x_test = test_data_frame[feature_columns].values 
    y_test = test_data_frame[predicted_column].values 

    x_train, x_test = impute(x_train, x_test) 

    return x_train, y_train, x_test, y_test 


def impute(x_train, x_test): 

    fill_missing = Imputer(missing_values=-9, strategy="mean", axis=0) 

    x_train = fill_missing.fit_transform(x_train) 
    x_test = fill_missing.fit_transform(x_test) 

    return x_train, x_test 


def predict(x_train, y_train, x_test, y_test): 

    model = GaussianNB() 
    model.fit(x_train, y_train.ravel()) 

    predicted_data = model.predict(x_test) 
    accuracy = metrics.accuracy_score(y_test, predicted_data) 
    print("Accuracy of our naive bayes model is : %.2f"%(accuracy * 100)) 

    return predicted_data 


feature_columns = ["age", "sex", "chol", "cigs", "years", "fbs", "trestbps", "restecg", "thalach", "exang", "oldpeak", "slope", "ca", "thal", "num"] 
predicted_column = ["cp"] 

x_train, y_train, x_test, y_test = load_data(feature_columns, predicted_column) 

predict(x_train, y_train, x_test, y_test)

N.B：两个文件具有相同的列数。

来源

2017-06-19 MD. Khairul Basar

你可以发布完整的堆栈跟踪吗？ – EFT

@EFT我已经发布了完整的追踪。顺便说一句，我刚刚发现'Imputer'正在删除一列，因为它完全由缺失值组成。有什么办法可以防止这种情况发生？ –

没有人在这里使用'read_excel（“training_data.xlsx”）''使用的文件。你能用公共数据集重现这个问题吗？ –

我发现了这个错误。由于Imputer，错误发生。 Imputer替换数据集中的缺失值。但是，如果任何列完全由缺失值组成，那么它将删除该列。我有一列完整的测试数据集中缺失的数据。因此，Imputer正在删除，因此形状与训练数据不匹配，这就是错误的原因。刚从feature_columns列表中删除了列名，该列表中充满了缺失值并且工作正常。

来源

2017-06-20 05:10:45

Scikit学习 - ValueError：操作数无法一起播放

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