Using different distances with evalclusters
14 visualizzazioni (ultimi 30 giorni)
Mostra commenti meno recenti
Manash Sahoo
il 5 Mag 2021
Risposto: Shraddha Jain
il 22 Giu 2021
Hey everyone!
I would like to use the evalclusters function with linkage method. However, the doc for the function states that specifying 'linkage' in input in evalclusters will use agglorometive clustering with ward's distance. However, I would like to use complete distance as opposed to ward's. I've tried this to no avail:
f = @(X)linkage(X,'complete');
eva = evalclusters(Data,f,'klist',[1:6]);
All this does is return an empty Evaluation object with NaNs as the outputs.
How would I go about specifying distance in these functions?
Any help would be great. Thanks!
0 Commenti
Risposta accettata
Shraddha Jain
il 22 Giu 2021
Hi Manash,
The second input argument clust in the function evalclusters refers to the clustering algorithm that is used.
When clust is specified as 'linkage', it means that clusterdata agglomerative clustering algorithm will be used to cluster the given input data x with the algorithm for computing the distance between clusters'Linkage' pre-defined to 'ward'.
This 'Linkage'algorithm could certainly be changed to something other than 'ward' by speifying it in a function handle using clusterdata and passing that as the clust argument in evalclusters,
f = @(x,k) clusterdata(x,'linkage','complete','maxclust',k);
eva = evalclusters(Data,f,'klist',[1:6]);
The reason that Ward Linkage is used as default in clusterdata as it the minimum variance method, therefore it minimizes the total within-cluster variance.
Hope this helps!
0 Commenti
Più risposte (0)
Vedere anche
Categorie
Scopri di più su Material Sciences in Help Center e File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!