I am trying to use clustering on my data but I do not have found the results I hoped for. I have a massive dataset with fire incidents. I would like to find clusters in these data. I want to use 4 categories to cluster the incidents. I would like to use the incident type, the response type, cause and the type of property. The result I am looking for is that the algorithm gives me clusters about types. Cluster 1: incidenttype A or incidenttype H, Responsetype X or Responsetype K , cause D and property R and so on. At this moment I tried to find this with K-means. But in the end I get clusters containing al most all categories of all four. Not nicely separated clusters. The first thought I have, is to check whether I use the best fitting algorithm?
I played around with different methods, and decided to go for K-means. Played around with the settings and I get what I was hoping for. I filtered out the characteristics which do not happen very often (only a few times) and this how the incdent types in the data getting some more structural shapes.
It gave me pretty good results. I think I can get better results by finding the right amount of K clusters.