synthetic

<p>This simple dataset allows users to use data that are easy to understand while learning
<code>biclustermd</code>. This is a matrix with 6 rows and 12 columns. 50% of values are missing.</p>

datasets

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.

John Reisner

biclustermd

Biclustering with Missing Data

Hieu Pham

Jing Li

synthetic function

<p>An object of class <code>matrix</code> with 6 rows and 12 columns.</p>

synthetic: Synthetic data for examples.

Description

Usage

Arguments

Format