f_score_calc: This function creates a summary metric for model training

In OHDSI/Aphrodite: Automated PHenotype Routine for Observational Definition Identification Training and Evaluation (APHRODITE) - Phenotype building tool using Fuzzy labels

Description

This function creates a new summary metric for model training, specific for unbalanced classes. Inputs as specified in caret.

Usage

f_score_calc(data, lev = levels(data$obs), model = NULL)

Arguments

data	A dataframe of the held-out example cases, with columns for 'obs', 'pred', 'T', 'F'. 'T' and 'F' have the probabilities of each of these classes
lev	Outcome factor levels for model
model	Character string of model used

Details

This function returns the F-score for model training optimization. Beta is currently set at 2 - TODO: should make this edit-able in future version.

Value

f_score

Examples

## Not run: 

 f_score <- f_score_calc(data, lev, model)


## End(Not run)

OHDSI/Aphrodite documentation built on Sept. 18, 2020, 10:26 p.m.