Biclustering with Missing Data // 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, 304316.