How to cluster a dataset having a vector of clustered indeces?
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Hello,
My question is very primitive, I'm trying to cluster my dataset using k-means and plot clastered data in heatmap.
I've tried to write the following primitive code but I don't understand why it is not working. Could you please help me figure out why my code is not working and what would be the shortest way to do this simple clustering?
Thank you!
n = 3; % specify the number of clusters that you want the dataset to be divided into
data = randi(100,10,9);
clust_idx = kmeans(data,n);
clustered = [];
for j = 1:n
for i = 1:length(clust_idx)
if clust_idx(i)==j, clustered = [clustered, (data(:,i))];
end
end
end
f = figure(1);
fh = heatmap((clustered)','XLabel','Time(min)','YLabel','Cell #','Colormap',jet);
2 件のコメント
Adam Danz
2019 年 4 月 11 日
1) What part of the code isn't working?
2) What does it mean that the code isn't working? Are you getting an error message (if yes, share the entire message)?
The first 3 lines of your code should workfine as long as you're working with decent data. What are the loops for?
採用された回答
Adam Danz
2019 年 4 月 11 日
編集済み: Adam Danz
2019 年 4 月 15 日
Your data is a matrix of size [10 x 9].
kmeans() identifies the cluster of each row of the matrix so its output will be a vector whose length is equal to the number of rows of your matrix (10 rows).
Your i-loop loops through each row (1:10). But your indexing your data by column: data(:,1). You only have 9 columns so on the last iteration, there's an error.
I think what you meant to write is:
clustered = [clustered; (data(i,:))];
% ^ ^ Note the restructuring.
Now your code works for the [10 x 9] inputs.
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