An implementation of classifier chains for binary and probabilistic multi-label prediction. The classification pipeline consists of:
Training an ensemble of classifier chains. Each chain is a binary classifier (built-in, supplied from an external package or user-coded).
Making predictions using a Gibbs sampler since each unobserved label is conditioned on the others.
(Optional) Evaluating the ECC.
Gathering predictions (aggregating across iterations & models).
To learn more about MLPUGS, start with the vignettes:
browseVignettes(package = "MLPUGS")
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