How to compute Receiving Operating Characteristic (ROC) and AUC in keras?

Question

I have a multi output(200) binary classification model which I wrote in keras.

In this model I want to add additional metrics such as ROC and AUC but to my knowledg

Answer 1

Set your model architecture with tf.keras.metrics.AUC(): Read following Keras Blog: Keras Page

def model_architecture_ann(in_dim,lr=0.0001):
    model = Sequential()
    model.add(Dense(512, input_dim=X_train_filtered.shape[1], activation='relu'))
    model.add(Dense(1, activation='sigmoid'))
    opt = keras.optimizers.SGD(learning_rate=0.001)
    auc=tf.keras.metrics.AUC()
    model.compile(loss='binary_crossentropy', optimizer=opt, metrics=[tf.keras.metrics.AUC(name='auc')])    
    model.summary()
    return model