Recursive Data Clustering through Finding Vague Solutions
Version 2 : Received: 13 May 2019 / Approved: 14 May 2019 / Online: 14 May 2019 (11:16:12 CEST)
How to cite: Monaco, D. Recursive Data Clustering through Finding Vague Solutions. Preprints 2019, 2019050142 (doi: 10.20944/preprints201905.0142.v2). Monaco, D. Recursive Data Clustering through Finding Vague Solutions. Preprints 2019, 2019050142 (doi: 10.20944/preprints201905.0142.v2).
- When we use an algorithm of clustering that can create a set of differents clustering, but equally valid and don’t know exctly what we must have as good solution, we areled to ask ourselves: ”What are the better?” This obviously depends by our goals, sonow the question is: ”What are our goals?”;
- The second problem is condensed in the sentence ”Not all clusters can be found in one-shot clustering process, more often we must reapply the process to some part of datataset”, so there we have a second question that this paper answering: ”How to create clustering of data with ad-hoc processing for each different part of input dataset?”;
These questions are resolved by the approaches named in this work as: Space of Solutions, Vague-Solution, Vague-Solution finding Method and finaly Recursive Clustering. All of these approaches was drafted and tested in mine Master Thesis titled ”Geospatial data analysis for Urban informatics applications: the case of the Google Place of the City of Milan” .
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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