Python 中的二元预测绘图不起作用

Question

我正在尝试使用 Python 为二元模型绘制一些数据，但图表没有显示任何数据，我不明白为什么，我没有错误，代码是运行非常快，二进制模式的结果是正确的，它向我显示了正确的数据，但没有绘制图表，我不明白为什么...这是我的 python 代码，我收到 ['acc']:

的关键错误

   #Building and Training the Neural Network
from keras.models import Sequential
from keras.layers import Dense
from keras.optimizers import Adam

# convert into binary classification problem - heart disease or no heart disease
Y_train_binary = y_train.copy()
Y_test_binary = y_test.copy()

Y_train_binary[Y_train_binary > 0] = 1
Y_test_binary[Y_test_binary > 0] = 1

print(Y_train_binary[:20])
        def create_binary_model():
            # create model
            model = Sequential()
            model.add(Dense(16, input_dim=13, kernel_initializer='normal', activation='relu'))
            model.add(Dense(8, kernel_initializer='normal', activation='relu'))
            model.add(Dense(1, activation='sigmoid'))

            # Compile model
            adam = Adam(lr=0.001)
            model.compile(loss='binary_crossentropy', optimizer=adam, metrics=['accuracy'])
            return model

        binary_model = create_binary_model()

        print(binary_model.summary())

        # fit the binary model on the training data
        history=binary_model.fit(X_train, Y_train_binary, validation_data=(X_test, Y_test_binary), epochs=200, batch_size=10, verbose = 10)

        import matplotlib.pyplot as plt
        # Model accuracy, here the graph it's not plotted
        plt.plot(history.history['acc'])
        plt.plot(history.history['val_acc'])
        plt.title('Model Accuracy')
        plt.ylabel('accuracy')
        plt.xlabel('epoch')
        plt.legend(['train', 'test'])
        plt.show()
        # Model Losss, here the graph it's not plotted
        plt.plot(history.history['loss'])
        plt.plot(history.history['val_loss'])
        plt.title('Model Loss')
        plt.ylabel('loss')
        plt.xlabel('epoch')
        plt.legend(['train', 'test'])
        plt.show()

        # generate classification report using predictions for categorical model
        from sklearn.metrics import classification_report, accuracy_score
        # generate classification report using predictions for binary model 
        binary_pred = np.round(binary_model.predict(X_test)).astype(int)

        print('Results for Binary Model')
        print(accuracy_score(Y_test_binary, binary_pred))
        print(classification_report(Y_test_binary, binary_pred))

这是图表现在的样子，它没有绘制我的数据：

它应该是这样的...:[=13=]

Answer 1

我其实不知道为什么，但我以前遇到过这个错误：有时模型历史记录中的准确性保持为 acc，有时保持为 accuracy。可能与编译模型时的metrics有关。在您的代码中它是 accuracy，因此您可以尝试使用：history.history['accuracy'] 而不是 acc。

Python 中的二元预测绘图不起作用

Plotting of binary prediction in Python it's not working

python

prediction

neural-network

keras