Which of the folowing is not an optimizer function?Stochastic Gradient Descent (SGD)RMSAdamRMSprop

To determine which of the options listed is not an optimizer function, let's analyze each one:

1. Stochastic Gradient Descent (SGD): This is an optimizer that updates the weights of a model based on the gradients of the loss function calculated with respect to a small sample of the training data. It is widely used in machine learning.

2. Adam: This stands for Adaptive Moment Estimation and is indeed an optimizer function. It combines the advantages of two other extensions of stochastic gradient descent: AdaGrad and RMSProp.

3. RMSprop: This is also an optimization algorithm that divides the learning rate by an exponentially decaying average of squared gradients, which helps in dealing with the problem of vanishing or exploding gradients.

Based on the analysis, all the provided options are well-known optimization functions with one exception. Thus, the final answer is that "RMS" is not a recognized optimizer function as it appears to be improperly abbreviated and does not correspond to a specific algorithm on its own.

If "RMS" intends to refer to RMSprop, then all mentioned terms are indeed optimizers. It seems there may have been a misunderstanding regarding "RMS" as a standalone term.