This point is basically a continuation of Issue #10. First we need to get more experienced with hierarchical clustering. Then we can see if it possible to create a final clustering in which we basically use multiple threshold to differentiate between different physical copies of the same camera and cameras that are from different brands. The idea is that the inter-cluster distance will be much larger for cameras that are from different brands. And that therefore we cannot use a single threshold in a large dataset with many different cameras, of which some belong to the same brand and/or model.
This point is basically a continuation of Issue #10. First we need to get more experienced with hierarchical clustering. Then we can see if it possible to create a final clustering in which we basically use multiple threshold to differentiate between different physical copies of the same camera and cameras that are from different brands. The idea is that the inter-cluster distance will be much larger for cameras that are from different brands. And that therefore we cannot use a single threshold in a large dataset with many different cameras, of which some belong to the same brand and/or model.