I have a dataset of workers, and I want to divide them into clusters based on some observables, one of them is categorical (industry). I'm trying to do k-mean clustering. Instead of using many dummy variables for the different categories, I built a similarity measure between each pair of industries and want to use it in the k-mean algorithm. My question is how can I use this pre-existing similarity matrix in the k-mean computation, together with other continuous variables (e.g., education). The way I'm doing it right now is first to collapse the similarity matrix into 2 or 3 dimensions using multidimensional scaling process and then use the results in the k-mean method. Is there a way to use the similarity matrix directly?
Related Posts with k-mean clustering using existing similarity matrix
M Jones ModelHi,Is the following code true for the m jones model? data: 2010-2017 for 35 country and 24 industry …
Tabs for multiple subgroups in one tableI am hoping to run tabs for by various subgroups (different job roles, in this instance). For my tw…
Grs testHi Statalist Members! I am conducting a research on variation of the average returns on 12 portfoli…
Generate spatial weight matrix by using "spweight"Hi everybody, I am working on Emad A. Shehata's spatial command modules, but I got a trouble in cre…
question on line chart outputHello, I created a twoway line chart but the output is too small and I'm not sure how to make it la…
Subscribe to:
Post Comments (Atom)
0 Response to k-mean clustering using existing similarity matrix
Post a Comment