`CBASS`

returns a fast approximation to the Convex BiClustering
solution path along with visualizations such as dendrograms and
heatmaps. `CBASS`

solves the Convex Biclustering problem using an efficient
Algorithmic Regularization scheme.

CBASS( X, ..., row_weights = sparse_rbf_kernel_weights(k = "auto", phi = "auto", dist.method = "euclidean", p = 2), col_weights = sparse_rbf_kernel_weights(k = "auto", phi = "auto", dist.method = "euclidean", p = 2), row_labels = rownames(X), col_labels = colnames(X), X.center.global = TRUE, t = 1.01, back_track = FALSE, exact = FALSE, norm = 2, npcs = min(4L, NCOL(X), NROW(X)), dendrogram.scale = NULL, status = (interactive() && (clustRviz_logger_level() %in% c("MESSAGE", "WARNING", "ERROR"))) )

X | The data matrix (\(X \in R^{n \times p}\)).
If |
---|---|

... | Unused arguements. An error will be thrown if any unrecognized arguments as given. |

row_weights | One of the following: A function which, when called with argument `X` , returns a n-by-n matrix of fusion weights.A matrix of size n-by-n containing fusion weights
Note that the weights will be renormalized to sum to \(1/\sqrt{n}\) internally. |

col_weights | One of the following: A function which, when called with argument `t(X)` , returns a p-by-p matrix of fusion weights. (Note the transpose.)A matrix of size p-by-p containing fusion weights
Note that the weights will be renormalized to sum to \(1/\sqrt{p}\) internally. |

row_labels | A character vector of length \(n\): row (observation) labels |

col_labels | A character vector of length \(p\): column (variable) labels |

X.center.global | A logical: Should |

t | A number greater than 1: the size of the multiplicative update to
the cluster fusion regularization parameter (not used by
back-tracking variants). Typically on the scale of |

back_track | A logical: Should back-tracking be used to exactly identify fusions? By default, back-tracking is not used. |

exact | A logical: Should the exact solution be computed using an iterative algorithm?
By default, algorithmic regularization is applied and the exact solution
is not computed. Setting |

norm | Which norm to use in the fusion penalty? Currently only |

npcs | An integer >= 2. The number of principal components to compute for path visualization. |

dendrogram.scale | A character string denoting how the scale of dendrogram
regularization proportions should be visualized.
Choices are |

status | Should a status message be printed to the console? |

An object of class `CBASS`

containing the following elements (among others):

`X`

: the original data matrix`n`

: the number of observations (rows of`X`

)`p`

: the number of variables (columns of`X`

)`alg.type`

: the`CBASS`

variant used`row_fusions`

: A record of row fusions - see the documentation of`CARP`

for details of what this may include.`col_fusions`

: A record of column fusions - see the documentation of`CARP`

for details of what this may include.