I have to identify the different operational states of a server. I have readings related to the different sensors of the server ( like temp sensor,fan speed sensor,job load sensor etc).The data I have information about some operational states (normal, high temp , high temp and high fan speed) etc. What ML algorithms should I use to identify if any other operational state,state which the training data has not seen, comes up?
I have used several clustering algorithms. I expected Gaussian Mixture models to work well, but they fail to indicate a new operational state of it comes up.
I used LSTM and looked at the residuals, but had to look at the residuals of each parameter to identify diff states.