suggest_best_k-ConsensusPartition-method {cola} | R Documentation

## Suggest the best number of subgroups

### 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 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.

### Author(s)

Zuguang Gu <z.gu@dkfz.de>

### Examples

    data(cola_rl)
    obj = cola_rl["SD", "kmeans"]
    suggest_best_k(obj)

[Package cola version 1.4.1 Index]