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GGiecold-zz / Cluster_Ensembles

A package for combining multiple partitions into a consolidated clustering. The combinatorial optimization problem of obtaining such a consensus clustering is reformulated in terms of approximation algorithms for graph or hyper-graph partitioning.
MIT License
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Set the K by user #7

Closed Jack-Lin-DS-AI closed 7 years ago

Jack-Lin-DS-AI commented 7 years ago

Currently, there is an option to define the maximum K of the cluster number (N_clusters_max). Is it possible to define K by user instead of estimating K by the algorithm? Thank you.

GGiecold-zz commented 7 years ago

Starting with a large value of K, run Cluster_Ensembles. If satisfied with the partition thereby obtained, stop. Otherwise, set K to a smaller value and repeat the procedure until a partition with a desired number of consensus clusters has been identified.

Gregory

On Oct 26, 2016 7:12 PM, "Chih-Hsu Lin" notifications@github.com wrote:

Currently, there is an option to define the maximum K of the cluster number (N_clusters_max). Is it possible to define K by user instead of estimating K by the algorithm? Thank you.

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Jack-Lin-DS-AI commented 7 years ago

Let me rephrase my question. I'd like to get and compare the the clustering results of two different Ks, e.g., K=2 and K=3. Is it possible?