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[D] Unsupervised Clustering without knowing number of classes (alien.top)

submitted 10 months ago by BigBrainUrinal@alien.top to c/machinelearning@academy.garden

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Does anyone know where to find the best models for unsupervised clustering problems that don't specify the number classes? For example I googled unsupervised MNIST but IIC which holds the record requires the output dimension (k=10) to be specified? Is there a name for unsupervised clustering without knowing the number of classes? (I know of density/hierarchical clustering algorithms but am unaware of many deep learning ones) And specifically are results charted anywhere? I'm researching the topic and it seems knowing the number of things you're looking for is half the battle. I can find papers on methods that aim to find the number of clusters etc but are there any benchmarks to compare?

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[–] BigBayesian@alien.top 1 points 10 months ago

Check out model selection. There’s heuristic scores that can work okay - AIC, BIC.

Basically, it comes down to trading off quality of fit (distance from datapoints to cluster means) with complexity of model.