View source: R/CC_with_robScore_functions.R

CC_cluster_count | R Documentation |

Count the number of clusters based on stability score.

```
CC_cluster_count(CM, plot.cdf = TRUE, plot.logit = FALSE)
```

`CM` |
list of consensus matrices each for a specific number of clusters.
It can be the output of |

`plot.cdf` |
binary value to plot the cumulative distribution functions of |

`plot.logit` |
binary value to plot the logit model of cumulative distribution functions of |

Count the number of clusters given a list of consensus matrices each for a specific number of clusters.
Using different methods: `"LogitScore", "PAC", "deltaA", "CMavg"`

results as a list:
`"LogitScore", "PAC", "deltaA", "CMavg"`

,
`"Kopt_LogitScore", "Kopt_PAC", "Kopt_deltaA", "Kopt_CMavg"`

```
X = gaussian_clusters()$X
Adj = adj_mat(X, method = "euclidian")
CM = consensus_matrix(Adj, max.cluster=3, max.itter=10)
Result = CC_cluster_count(CM, plot.cdf=FALSE)
```

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