CODEWITHSUNDEEP
cluster-analysishierarchical-clusteringonline-algorithm
Masood_mj
Masood_mj

Reputation: 1184

Clustering with varying dimensions

In my clustering problem, not only the points can come and go but also the features can be removed or added. Is there any clustering algorithm for my problem.

Specifically I am looking for an agglomerative hierarchical clustering version of these kind of clustering algorithms.

Upvotes: 0

Views: 153

Answers (1)

Has QUIT--Anony-Mousse
Has QUIT--Anony-Mousse

Reputation: 77485

You can use hierarchical clustering (except it scales really bad) or any other distance based clustering. Just k-means is a bit tricky because how do you compute the mean when the value is not present?

You only need to define an appropriate distance function first.

Clustering is usually done based on similarity, so: first find out what "similar" means for you. This is very data set and use case specific, although many people can use some kind of distance function. There is no "one size fits all" solution.

Upvotes: 0

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