tidysdm (version 1.0.0)

calib_class_thresh: Calibrate class thresholds

Description

Predict for a new dataset by using a simple ensemble. Predictions from individual models are combined according to fun

Usage

calib_class_thresh(object, class_thresh, metric_thresh = NULL)

Value

a simple_ensemble object

Arguments

object

an simple_ensemble object

class_thresh

probability threshold used to convert probabilities into classes. It can be a number (between 0 and 1), or a character metric (currently "tss_max", "kap_max" or "sensitivity"). For sensitivity, an additional target value is passed along as a second element of a vector, e.g. c("sensitivity",0.8).

metric_thresh

a vector of length 2 giving a metric and its threshold, which will be used to prune which models in the ensemble will be used for the prediction. The 'metrics' need to have been computed when the workflow was tuned. The metric's threshold needs to match the value used during prediction. Examples are c("accuracy",0.8) or c("boyce_cont",0.7).

Examples

test_ens <- simple_ensemble() %>%
  add_member(two_class_res[1:3, ], metric = "roc_auc")
test_ens <- calib_class_thresh(test_ens, class_thresh = "tss_max")
test_ens <- calib_class_thresh(test_ens, class_thresh = "kap_max")
test_ens <- calib_class_thresh(test_ens, class_thresh = c("sens", 0.9))