I guess LSTM is good for sequence modeling but how would you model clustering with it? Meaning, the input is a sequence and the output is labels with similar properties (I have labeled data). For example: input:  1 2 1 1 2 1 2 5 6 5 4 5 1 1 2 1 1 2 1 output: 1 1 1 1 1 1 1 2 2 2 2 2 1 1 1 1 1 1 1The problem is how to tell the model to learn differences and not the particular example, as a new example could have totally different values. I could have taught it to predict the N*(N-1)/2 pairwise differences (similar non similar) but it will not learn the dynamics.
How to model segmentation of a sequence to similar parts?
machine learning;neural network;deep learning