bm_msrtab: Benchmark result performance measures table

In NaiaraLopezRojo/globalIRmap: What the Package Does (One Line, Title Case)

Description

Get hyperparameters and performance measures for every ResampleResult in a BenchmarkResult of classification models.

Usage

bm_msrtab(bmres, interthresh = NULL)

Arguments

bmres	BenchmarkResult from either a binary classification model or a regression model bounded between 0 and 1.
interthresh	(numeric) between 0 and 1 (inclusive), threshold to compute sensitivity, specificity, and balanced accuracy. If not provided, specificity and sensitivity will be provided for a 0.5 threshold and the highest BACC for thresholds ranging from 0.45 to 0.55 will be provided.

Details

performance measures include Binary brier score (bbrier), Area Under the ROC Curve (AUC), sensitivity, specificity, and Balanced classification ACCuracy (BACC).

Value

data.table of model hyperparameters and measure performance values for each ResampleResult.

See Also

bm_paramstime, rsmp_bbrier, rsmp_auc, rsmp_sen, rsmp_spe, rsmp_bacc

NaiaraLopezRojo/globalIRmap documentation built on Dec. 17, 2021, 5:19 a.m.