fill_empties_P

The data being biclustered. Must to be a data matrix with only numbers and missing values in the data set. It should have row names and column names.

data

A matrix for column clusters, typically named P.

Minimum column prototype size in order to be eligible to be chosen when filling an empty column prototype. Default is 10.

col_min_num

Number of columns to remove from the sampled prototype to put in the empty column prototype. Default is 5.

col_num_to_move

Randomly select a column prototype to fill an empty column prototype with

Biclustering is a statistical learning technique that simultaneously
partitions and clusters rows and columns of a data matrix. Since the solution
space of biclustering is in infeasible to completely search with current
computational mechanisms, this package uses a greedy heuristic. The algorithm
featured in this package is, to the best our knowledge, the first biclustering
algorithm to work on data with missing values. Li, J., Reisner, J., Pham, H.,
Olafsson, S., and Vardeman, S. (2020) Biclustering with Missing Data. Information
Sciences, 510, 304<e2><80><93>316.

fill_empties_P: Randomly select a column prototype to fill an empty column prototype with

Description

Usage

Arguments

Value