title: Is there a clustering method that can find an interpretable optimal subspace?
body: <p>I'm looking for a clustering method than can find an interpretable optimal subspace.For example, if I have a dataset consistes of some features [feature_1, feature_2,...,feature_n], after clusering, I can get a clustering result and a subspace [feature_3, feature_6,...,feature_9], this subspace can interpret why any one of clustering can be clustered together.</p>
  
  <p>I've tried subkmeans, it is similar with PCA, but subkmeans will transform the original dataset, although it can find an optimal subspace. Since subkmeans transformed my dataset that result in I can't find the corresponding features(that is subspace I need), so I what to ask is there a clustering method that can find this subspace.</p>