docs/functions/assess.md

In jgygi/SPEAR: SPEAR - Sparse Supervised Bayesian Factor Model for Multi-omic Analyses

assess

Assess the predictions from the SPEAR model using a variety of metrics. Utilizes the 'yardstick' package under the 'tidymodels' umbrella.

Description

Assess the predictions from the SPEAR model using a variety of metrics. Utilizes the 'yardstick' package under the 'tidymodels' umbrella.

Usage

assess(data = "train", cv = TRUE, estimator = "macro", metrics = NULL)

Arguments

Argument |Description ------------- |---------------- data | Which dataset to use? Can be any dataset listed under $data$____. Defaults to "train". cv | If data = "train", get factor scores generated from $run.cv.spear? If $run.spear was used or if data != "train" this parameter is ignored. Defaults to TRUE. estimator | Estimator for the yardstick metrics. Can be "macro", "micro", or "macro_weighted". Note that some metrics ignore these. metrics | A vector of metrics to use. See https://yardstick.tidymodels.org/articles/metric-types.html for all possibilities.

jgygi/SPEAR documentation built on July 5, 2023, 5:35 p.m.