Open benvanwerkhoven opened 8 years ago
There is also the concept of pareto optimality, where you optimize on an arbitrary number of objectives simultaneously, while gaining (some) insight into the tradeoffs between objectivives (what does a metric measure?).
We currently do not know which similarity metrics is the 'best'. Perhaps it differs per dataset or per clustering algorithm that you use afterwards. What are the benefits of using one metric over the other? It would be very good if someone could look into this.