Info

此问题已关闭。 请重新打开它进行编辑或回答。

k means clustering: Classifying subsequent to a particular cluster - can it be done?

4 次查看（过去 30 天）
John
John 2011-11-16
关闭： MATLAB Answer Bot 2021-8-20
Hi there,
I have question in relation to k means clustering. Say I created two clusters from data. For example using this code:
X = [randn(100,2)+ones(100,2);...
randn(100,2)-ones(100,2)];
opts = statset('Display','final');
[idx,ctrs] = kmeans(X,2,...
'Distance','city',...
'Replicates',5,...
'Options',opts);
plot(X(idx==1,1),X(idx==1,2),'r.','MarkerSize',12)
hold on
plot(X(idx==2,1),X(idx==2,2),'b.','MarkerSize',12)
plot(ctrs(:,1),ctrs(:,2),'kx',...
'MarkerSize',12,'LineWidth',2)
plot(ctrs(:,1),ctrs(:,2),'ko',...
'MarkerSize',12,'LineWidth',2)
legend('Cluster 1','Cluster 2','Centroids',...
'Location','NW')
My question is, if you collect more data can you assign it to each of the two clusters that have already been formed, or do you have to cluster all of the data again?
If it is possible, how would you do it?
Thank you

此问题已关闭。

回答（1 个）

Wayne King
Wayne King 2011-11-16
k-means is an unsupervised learning algorithm that is sensitive to the number of clusters you choose AND to the initial start centers. I would say that you would need to cluster the data again.

此问题已关闭。

标签

Community Treasure Hunt

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

Start Hunting!

Translated by