How to aasign a new data point to a cluster? I have a userdataset which contains fields like ['age','gender', 'computer_literacy', 'vision', 'colour_blind', 'education', 'font_size','colour'].
I clustered these data and assigned the new cluster to the existing data. Now I want to know how can I find a similar cluster for a new user?
As an example, If I am a new user I only submit few details like ['age', 'gender', 'computer_literacy', 'vision'] and I want to know, for which cluster I belong.
What are the possible approaches to solve this problem?
Suppose if  you use kmeans clustering then you can
1.train and  save the model using pickle
2.loa the model using pickle
3.pass your new sample as a vector to the predict function of the loaded model  object
model.predict([[0, 0], [12, 3]])
this will give you only one cluster label
4.if you want to get  top n clusters that the sample might belong to then take the cluster centers of your model as save it in a variable this will be list of list or matrix .
cc=kmeans.cluster_centers_
compute the similarity between your new sample and the cc matrix , rank the distances and yo will get n nearest clusters