Different Values if K-means Clustring on same data.
1 次查看(过去 30 天)
显示 更早的评论
I have been using matlab function of K-means clustring for making clusters of data. I happen to apply it on same data. But got wildly different results every time. I know the reason for this. But I need sugestions for overcoming this issue. Should I use some modified version of K-means or Should look for some other clustering technique?
K-means command which i used is "kmeans(Feature_Matrix,20,'Replicates',5,'emptyaction','singleton');
0 个评论
采纳的回答
Shashank Prasanna
2014-4-8
编辑:Shashank Prasanna
2014-4-8
Kmeans can get stuck in local minima. By which I mean it is sensitive to initial centroid positions. You can specify a higher number of replicates to increase you chances of getting a global solution.
If you are interested in exploring other clustering algorithms, find all the supported ones here:
2 个评论
Walter Roberson
2014-4-8
kmeans uses random initialization of cluster positions, unless you pass it specific positions to start at.
更多回答(0 个)
另请参阅
类别
在 Help Center 和 File Exchange 中查找有关 Statistics and Machine Learning Toolbox 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!