I want to cluster image, since varibility intra and inter class of images is huge I think reducing dimensions with a convolutional autoencodeur can be a good tools. Then I apply clustering on the feature vector
My question: is there a theorical link between my convolutional autoencodeur loss and the potential for clustering of my extracted feature vector?
To add more detail, can we says if I can minimise loss then it'll be easier to do clustering on feature vector? My intuition tel me answer is NO
But if we can't use loss to select potential best model for clustering, then isn't it almost impossible to do a good clustering using this methodology?