weighted binary crossentropy keras
one_weight = (1-num_of_ones)/(num_of_ones + num_of_zeros)
zero_weight = (1-num_of_zeros)/(num_of_ones + num_of_zeros)
def weighted_binary_crossentropy(zero_weight, one_weight):
def weighted_binary_crossentropy(y_true, y_pred):
b_ce = K.binary_crossentropy(y_true, y_pred)
# weighted calc
weight_vector = y_true * one_weight + (1 - y_true) * zero_weight
weighted_b_ce = weight_vector * b_ce
return K.mean(weighted_b_ce)
return weighted_binary_crossentropy