| ari | Computes the adjusted Rand index and the confidence interval, comparing two classifications from a contingency table. |
| cc_crossclustering | A partial clustering algorithm with automatic estimation of the number of clusters and identification of outliers |
| cc_get_cluster | Provides the vector of clusters' ID to which each element belong to. |
| cc_get_cluster.crossclustering | Provides the vector of clusters' ID to which each element belong to. |
| cc_get_cluster.default | Provides the vector of clusters' ID to which each element belong to. |
| cc_test_ari | A test for testing the null hypothesis of random agreement (i.e., adjusted Rand Index equal to 0) between two partitions. |
| cc_test_ari_permutation | A permutation test for testing the null hypothesis of random agreement (i.e., adjusted Rand Index equal to 0) between two partitions. |
| chain_effect | A toy dataset for illustrating the chain effect. |
| consensus_cluster | Get clusters which reach max consensus |
| is_zero | Check for zero |
| nb_data | RNA-Seq dataset example |
| print.ari | Computes the adjusted Rand index and the confidence interval, comparing two classifications from a contingency table. |
| print.crossclustering | A partial clustering algorithm with automatic estimation of the number of clusters and identification of outliers |
| prune_zero_tail | Prune tail made of zeros |
| reverse_table | Reverse the process of create a contingency table |
| toy | A toy example matrix |
| twomoons | A famous shape data set containing two clusters with two moons shapes and outliers |
| worms | A famous shape data set containing two clusters with two worms shapes and outliers |