BayesMallows: assign_cluster – R documentation

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BayesMallows

assign_cluster

Assign Assessors to Clusters

Description

Assign assessors to clusters by finding the cluster with highest posterior probability.

Usage

assign_cluster(
  model_fit,
  burnin = model_fit$burnin,
  soft = TRUE,
  expand = FALSE
)

Arguments

`model_fit`	An object of type `BayesMallows`, returned from `compute_mallows`.
`burnin`	A numeric value specifying the number of iterations to discard as burn-in. Defaults to `model_fit$burnin`, and must be provided if `model_fit$burnin` does not exist. See `assess_convergence`.
`soft`	A logical specifying whether to perform soft or hard clustering. If `soft=TRUE`, all cluster probabilities are returned, whereas if `soft=FALSE`, only the maximum a posterior (MAP) cluster probability is returned, per assessor. In the case of a tie between two or more cluster assignments, a random cluster is taken as MAP estimate.
`expand`	A logical specifying whether or not to expand the rowset of each assessor to also include clusters for which the assessor has 0 a posterior assignment probability. Only used when `soft = TRUE`. Defaults to `FALSE`.

Value

A dataframe. If soft = FALSE, it has one row per assessor, and columns assessor, probability and map_cluster. If soft = TRUE, it has n_cluster rows per assessor, and the additional column cluster.