Data Science, Loss Function, Machine Learning, Neural Networks, TensorFlow.
up the learning process. def matrix_based_crossentropy (output, target, matrixA, from_logits = False): Loss = 0 ColumnVector = np.matul(matrixA, target) for i, y in enumerate (output): Loss -= (target[i]*math.log(output[i],2)) Loss += ColumnVector[i]*exponential(output[i]) Loss -=