compareEnsemble: Compare performance of several ensembles on the same data,...
In AleMorales/SeedSorter: Supervised classification of seeds from flow cytometry

Description Usage Arguments Details Value

Compare performance of several ensembles on the same data, with or without hyperparameter tuning

1	compareEnsemble(algorithms, task, tuning = FALSE, control = list())

`algorithms`	Vector with lists of algorithms to be stacked (same algorithms as in `trainAlgorithm()`).
`task`	Either one classification task for comparison using cross-validation or a list of tasks for comparisons across tasks (see Details).
`tuning`	Whether to tune the learners or not (default: `FALSE`).
`control`	Optional list of settings (see Details).

See compareAlgorithms(). The argument algorithms should be assigned a list of vectors (or list of lists). A stacked ensemble will be created for every element of the outer list.

The result of the comparison, as an object of class mlr::BenchmarkResult.

AleMorales/SeedSorter documentation built on Feb. 12, 2020, 4:13 a.m.