dahl-salso 0.5.6

The SALSO algorithm is an efficient greedy search procedure to obtain a clustering estimate based on a partition loss function. The algorithm is implemented for many loss functions, including the Binder loss and a generalization of the variation of information loss, both of which allow for unequal weights on the two types of clustering mistakes. Efficient implementations are also provided for Monte Carlo estimation of the posterior expected loss of a given clustering estimate. SALSO was first presented at the workshop 'Bayesian Nonparametric Inference: Dependence Structures and their Applications' in Oaxaca, Mexico on December 6, 2017.

dahl-salso's sandbox limits

All the builds on docs.rs are executed inside a sandbox with limited resources. The limits for this crate are the following:

Available RAM 3 GB
Maximum rustdoc execution time 15 minutes
Maximum size of a build log 100 KB
Network access blocked
Maximum number of build targets 10

If a build fails because it hit one of those limits please open an issue to get them increased.