保存线性回归的.pkl模型时出错

Question

我正在使用framworks django编码Web应用程序，问题是将线性再学习模型保存为.pkl时出现了问题。 是否需要创建一个空的.pkl文件或它会自动生成？以及如何读取此类.pkl文件的内容？

# Libraries

# Importing Dataset

    data = pd.read_csv('ml_code/ml_process/test.csv')
    data.fillna(0, inplace=True)


    def handle_non_numerical_data(df):
        columns = df.columns.values

        for column in columns:
            text_digit_vals = {}

            def convert_to_int(val):
                return text_digit_vals[val]

            if df[column].dtype != np.int64 and df[column].dtype != 
    np.float64:
                column_contents = df[column].values.tolist()
                unique_elements = set(column_contents)
                x = 0
                for unique in unique_elements:
                    if unique not in text_digit_vals:
                        text_digit_vals[unique] = x
                        x = x + 1

                df[column] = list(map(convert_to_int, df[column]))

        return df

    data = handle_non_numerical_data(data)
    data = data.as_matrix()

    #X matrice des var. explicatives
    X = data[:,0:9]
    #y vecteur de la var. à prédire
    y = data[:,9]

    X2_train, X2_test, y2_train, y2_test = train_test_split(X, y, 
    test_size=0.3, random_state=0)

    lreg = LinearRegression()

    lreg.fit(X2_train, y2_train)
    print('Accuracy of linear regression on training set: 
    {:.2f}'.format(lreg.score(X2_train, y2_train)))
    print('Accuracy of linear regression on test set: 
    {:.2f}'.format(lreg.score(X2_test, y2_test)))
    y_pred2 = lreg.predict(X2_test)
    print("Predicted Sales: %.3f" % (y_pred2[0]))
    ```   


Saving the Logistic Regression Model

linear_regression_model = pickle.dumps(lreg)

Saving the model to a file

joblib.dump(linear_regression_model,'ml_code/linear_regression_model.pkl')

I get this error when I run the application 

with open(filename, 'rb') as f:
FileNotFoundError: [Errno 2] No such file or directory: 
'ml_code/linear_regression_model.pkl'