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

90 次查看(过去 30 天)
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.

采纳的回答

kira
kira 2019-5-2
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);

更多回答(1 个)

Saranya  A
Saranya A 2018-3-8
编辑:KSSV 2021-2-11
This function will help you to find the optimum number of clusters. https://in.mathworks.com/matlabcentral/fileexchange/49489-best-kmeans-x-

类别

Help CenterFile Exchange 中查找有关 Cluster Analysis and Anomaly Detection 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by