algorithm - Can k-means clustering do classification? -


i want know whether k-means clustering algorithm can classification?

if have done simple k-means clustering .

assume have many data , use k-means clusterings, 2 clusters a, b. , centroid calculating method euclidean distance.

cluster @ left side.

cluster b @ right side.

so, if have 1 new data. should do?

  1. run k-means clustering algorithm again, , can cluster new data belong to?

  2. record last centroid , use euclidean distance calculating decide new data belong to?

  3. other method?

the simplest method of course 2., assign each object closest centroid (technically, use sum-of-squares, not euclidean distance; more correct k-means, , saves sqrt computation).

method 1. fragile, k-means may give different solution; in particular if didn't fit data in first place (e.g. high dimensional, clusters of different size, many clusters, ...)

however, following method may more reasonable:

3. train actual classifier.

yes, can use k-means produce initial partitioning, assume k-means partitions reasonable classes (you really should validate @ point though), , continue if data have been user-labeled.

i.e. run k-means, train svm on resulting clusters. use svm classification.

k-nn classification, or assigning each object nearest cluster center (option 1) can seen simple classifiers. latter 1nn classifier, "trained" on cluster centroids only.


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