CODEWITHSUNDEEP
pythonalgorithmscikit-learnk-means
deltascience
deltascience

Reputation: 3380

get the ith cluster after performing K-means algorithm in python

I have multiple points in a matrix that I tried to classify using K-means algorithm using 'scikit-learn' library in Python. Here is what I've done so far :

k_means = KMeans(init='k-means++', k=5, n_init=10)
k_means.fit(X) ## X is the matrix containing the data
... # some code to plot

The result is the following :

enter image description here

Now I want to get the points that are in the "red" cluster for example. How can I do that with sklearn ?

Upvotes: 1

Views: 1804

Answers (2)

deltascience
deltascience

Reputation: 3380

I think I found it. It simple: the object km have severale attributes. Among those attributes there is labels that gives for every point to which cluster it belongs:

km_labels = km.labels_
#to get all the items in the first cluster just get the indexes int km_labels with the

#value = 1

index = [x[0] for x, value in numpy.ndenumerate(km_labels) if value==1]

Upvotes: 1

Malcolm Murdoch
Malcolm Murdoch

Reputation: 1085

KMeans is a formula rather than a database. By that I mean it doesn't keep a record of the value for each record, it records a function that will assign the cluster given the input again. To get cluster assignment,there's a method called 'predict'.

kmeans.predict(value)

This will give you the cluster assignment from kmeans. If you iterate through your points you should be able to get them.

Upvotes: 1

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