我就废话不多说了,大家还是直接看代码吧~
import tensorflow as tf
from sklearn.metrics import roc_auc_score
def auroc(y_true..., y_pred):
return tf.py_func(roc_auc_score, (y_true, y_pred), tf.double)
# Build Model......model.compile(loss='categorical_crossentropy', optimizer='adam',metrics=['accuracy', auroc])
完整例子:
def auc...(y_true, y_pred):
auc = tf.metrics.auc(y_true, y_pred)[1]
K.get_session().run(tf.local_variables_initializer...adam = optimizers.Adam(lr=0.01)
model.compile(optimizer=adam,loss='binary_crossentropy',metrics = [auc