[scikit-learn] Using KMeans cluster labels in KNN

[prince gosavi]

Hi,
Thank you for reply.

I was exploring the possibility that given well formed KMean clusters using
an additional KNN we can simply increase the accuracy that the data point
enters the right cluster.

Also I would like to know whether if it's possible to do such thing(out of
curiosity)?


On Mon, Mar 12, 2018 at 4:16 PM, Sebastian Raschka <se.raschka at gmail.com>
wrote:

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> Hi,
> If you want to predict the Kmeans cluster membership, you can use Kmeans'
> predict method instead of training a KNN model on the cluster assignments.
> This will be computationally more efficient and give you the correct
> assignment at the borders between clusters.
>
> Best,
> Sebastian
>
> > On Mar 12, 2018, at 2:55 AM, prince gosavi <princegosavi12 at gmail.com>
> wrote:
> >
> > Hi,
> > I have generated clusters using the KMeans algorithm and would like to
> use the labels of the model in the KNN.
> >
> > I don't have the implementation idea but I can visualize it as
> >
> > KNNmodel = KNN.fit(X, KMeansModel.labels_)
> >
> > Such that the KNN will predict the cluster the new point belong to.
> >
> > --
> > Regards
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-- 
Regards
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