This class contains all the input options and common output options for all kinds of data-sets (Binary, Categorical, Contingency and Continuous).
Input data.
Type of data.
Boolean value specifying if Co-clustering is semi-supervised or not.
Model to be run for co-clustering.
Number of row and column clusters.
Input strategy.
Status returned.
Vector of row proportions.
Vector of column proportions.
Vector of assigned row cluster to each row.
Vector of assigned column cluster to each column.
Final pseudo log-likelihood.
Final posterior probabilities for rows.
Final posterior probabilities for columns.