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How to find optimal k from k means clustering by using elbow method

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I want to find optimal k from k means clustering by using elbow method . I have 100 customers and each customer contain 8689 data sets. How can I create a program to cluster this data set into appropriate k groups.

Accepted Answer

kira
kira on 2 May 2019
old question, but I just found a way myself looking at matlab documentation:
klist=2:n;%the number of clusters you want to try
myfunc = @(X,K)(kmeans(X, K));
eva = evalclusters(net.IW{1},myfunc,'CalinskiHarabasz','klist',klist)
classes=kmeans(net.IW{1},eva.OptimalK);

More Answers (1)

Saranya  A
Saranya A on 8 Mar 2018
Edited: KSSV on 11 Feb 2021
This function will help you to find the optimum number of clusters. https://in.mathworks.com/matlabcentral/fileexchange/49489-best-kmeans-x-

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