available_algorithms: Available Algorithms

In rtemis: Schema-Driven Machine Learning and Visualization

Available Algorithms

Description

Print available algorithms for supervised learning, clustering, and decomposition.

Usage

available_supervised(verbosity = 1L)

available_clustering(verbosity = 1L)

available_calibration(verbosity = 1L)

available_decomposition(verbosity = 1L, traits = FALSE)

Arguments

verbosity	Integer: Verbosity level.
traits	Logical: If TRUE, available_decomposition() prints and returns the full trait table from decomposition_traits instead of the named list of descriptions.

Details

Each algorithm is set up with ⁠setup_{Algorithm}()⁠, using the name printed here: setup_LightGBM(), setup_KMeans(), setup_PCA(). Pass the result to train, cluster, or decomp.

Value

Named list of algorithm descriptions, invisibly.

Author(s)

EDG

Examples

available_supervised()
# Train with one of them, at its default hyperparameters:
# train(iris, hyperparameters = setup_LightGBM())
available_clustering()
available_calibration()
# Calibrate with one of them:
# calibrate(mod, hyperparameters = setup_Isotonic())
available_decomposition()
available_decomposition(traits = TRUE)

rtemis documentation built on Oct. 20, 2026, 1:06 a.m.