neg_gmpa

See <code><a rd-options="" href="/link/error_fun?package=emil&version=2.2.10" data-mini-rdoc="emil::error_fun">error_fun</a></code>.

truth

prediction

Whether to remove missing values or not.

na.rm

When dealing with imbalanced classification problem, i.e. where the class
sizes are very different, small classes tend to be overlooked when tuning
parameters by optimizing error rate. Blagus and Lusa (2013) suggested to
remedy the problem by using this performance measure instead.

A toolbox for designing and evaluating predictive models with
resampling methods. The aim of this package is to provide a simple and
efficient general framework for working with any type of prediction
problem, be it classification, regression or survival analysis, that is
easy to extend and adapt to your specific setting. Some commonly used
methods for classification, regression and survival analysis are included.

Christofer Backlin

emil

Evaluation of Modeling without Information Leakage

Mats Gustafsson

neg_gmpa function

See <code><a rd-options='' href='error_fun'>error_fun</a></code>.

neg_gmpa: Negative geometric mean of class specific predictive accuracy

Description

Usage

Arguments

Value

References

See Also