suggest_best_k-ConsensusPartition-method: Suggest the best number of subgroups

In cola: A Framework for Consensus Partitioning

Description

Suggest the best number of subgroups

Usage

## S4 method for signature 'ConsensusPartition'
suggest_best_k(object, jaccard_index_cutoff = 0.95)

Arguments

object	A ConsensusPartition-class object.
jaccard_index_cutoff	The cutoff for Jaccard index for comparing to previous k.

Details

The best k is selected according to following rules:

• All k with Jaccard index larger than 0.95 are removed because increasing k does not provide enough extra information. If all k are removed, it is marked as no subgroup is detected.

• For all k with 1-PAC score larger than 0.9, the maximal k is taken as the best k, and other k are marked as optional k.

• If it does not fit the second rule. The k with the maximal vote of the highest 1-PAC score, highest mean silhouette, and highest concordance is taken as the best k.

Additionally, if 1-PAC for the best k is larger than 0.9 (10% ambiguity for the partition), cola marks it as a stable partition. It should be noted that it is difficult to find the best k deterministically, we encourage users to compare results for all k and determine a proper one which best explain their studies.

Value

The best k.

See

The selection of the best k can be visualized by select_partition_number.

Author(s)

Zuguang Gu <[e-mail]>

Examples

data(golub_cola)
obj = golub_cola["ATC", "skmeans"]
suggest_best_k(obj)

cola documentation built on Nov. 8, 2020, 8:12 p.m.