How to interpret loss and accuracy for a machine learning model
Then naturally, the main objective in a learning model is to reduce (minimize) the loss function's value with respect to the model's parameters by changing the weight vector values through different …
What is a loss function in simple words? - Stack Overflow
Can anyone please explain in simple words and possibly with some examples what is a loss function in the field of machine learning/neural networks? This came out while I was following a Tensorflow
machine learning - Common causes of nans during training of neural ...
Faulty Loss function Reason: Sometimes the computations of the loss in the loss layers causes nan s to appear. For example, Feeding InfogainLoss layer with non-normalized values, using custom loss …
machine learning - What is the difference between loss function and ...
Jan 16, 2018 · The loss function is that parameter one passes to Keras model.compile which is actually optimized while training the model . This loss function is generally minimized by the model.
machine learning - Low f1 score and also low loss function score ...
Aug 1, 2023 · Unfortunately after several hours of training (4 epochs), I suffer from a f1 score of only 0.04214842148421484. my final loss score is 0.00354736 I know that the loss function and the f1 …
How to correct unstable loss and accuracy during training?
Apr 29, 2019 · During training, the loss sometimes increases within the same epoch, leading to unstable learning. The accuracy hits a plateau around 70%. I have tried changing the learning rate and other …
Why does my training loss have regular spikes? - Stack Overflow
Dec 15, 2017 · Why does this matter? The model I am training, SSD, uses a rather complicated multi-task loss function that does its own averaging (not by the batch size, but by the number of ground …
machine learning - What would be a good loss function to penalize the ...
Jun 6, 2018 · Or maybe I misinterpreted the "x" and "y"? Hey Ethan. You’re right, this description wasn’t complete. The function elliptic_paraboloid_loss is a scaling factor that could be applied to any loss …
machine learning - What is cross-entropy? - Stack Overflow
I know that there are a lot of explanations of what cross-entropy is, but I'm still confused. Is it only a method to describe the loss function? Can we use gradient descent algorithm to find the minimum …
How to penalize False Negatives more than False Positives
23 There are several options for you: As suggested in the comments, class_weight should boost the loss function towards the preferred class. This option is supported by various estimators, including …