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Results tagged with clustering
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user 265510
Cluster analysis is the task of partitioning data into subsets of objects according to their mutual "similarity," without using preexisting knowledge such as class labels. [Clustered-standard-errors and/or cluster-samples should be tagged as such; do NOT use the "clustering" tag for them.]
2
votes
1
answer
712
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Mini batch K means: how is it guaranteed that at the end every element is labeled?
I'm trying to completely understand Mini Batch K means
After reading the following pseudo code ...
We all know that in every iteration, you choose a fixed size batch with a random set of elements …
- 269
8
votes
which metrics are suitable for density-based clustering validation?
I know it's a little bit late but I just wanted to say that I'm currently studying density based clustering algorithms, and I found out the most suitable metric was in fact DBCV:
1) it deals with noise … (which is intrinsic to the definition of the density-based clustering, and it's not taken into account in indexes such as Silhouette or Davies Bouldin)
2) it allows you to capture the shape of each cluster …
- 269
1
vote
1
answer
2k
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How come Mini Batch K means partial_fit method be useful for stream clustering?
Currently, I'm studying the advance in cluster analysis regarding stream clustering. … I ended up assessing Mini batch K means because of some comments I read on the Internet, like the following one:
Many clustering algorithms can be tweaked to be suitable for stream clustering. …
- 269