balancedaccuracy

This function calculates classification accuracy scores using the sine-based
formulas proposed by Starovoitov and Golub (2020). The advantage of the new
method consists in producing improved results when compared with the standard
balanced accuracy function, by taking into account the class distribution of
errors.

metric

balanced

score

accuracy

sine

Allows users to create weighted confusion matrices and accuracy
metrics that help with the model selection process for classification
problems, where distance from the correct category is important. The
package includes several weighting schemes which can be parameterized, as
well as custom configuration options. Furthermore, users can decide
whether they wish to positively or negatively affect the accuracy score
as a result of applying weights to the confusion matrix. Functions are
included to calculate accuracy metrics for imbalanced data. Finally,
'wconf' integrates well with the 'caret' package, but it can also work
standalone when provided data in matrix form.
References:
Kuhn, M. (2008) "Building Perspective Models in R Using the caret Package"
<doi:10.18637/jss.v028.i05>
Monahov, A. (2021) "Model Evaluation with Weighted Threshold Optimization
(and the mewto R package)" <doi:10.2139/ssrn.3805911>
Monahov, A. (2024) "Improved Accuracy Metrics for Classification with
Imbalanced Data and Where Distance from the Truth Matters, with the wconf R
Package" <doi:10.2139/ssrn.4802336>
Starovoitov, V., Golub, Y. (2020). New Function for Estimating Imbalanced
Data Classification Results. Pattern Recognition and Image Analysis, 295–302
Van de Velden, M., Iodice D'Enza, A., Markos, A., Cavicchia, C. (2023)
"A general framework for implementing distances for categorical variables"
<doi:10.48550/arXiv.2301.02190>.

Alexandru Monahov

wconf

Weighted Confusion Matrix

balancedaccuracy function

<dl><dt>m</dt>
<dd>the caret confusion matrix object or simple matrix.</dd>
<dt>print.scores</dt>
<dd>print the accuracy metrics.</dd></dl>

Arguments

Alexandru Monahov, &lt;https://www.alexandrumonahov.eu.org/&gt;

Author

Starovoitov-Golub Sine-Accuracy Function for Imbalanced Classification Data — balancedaccuracy

<dl>

<dt>m</dt>
<dd>the caret confusion matrix object or simple matrix.</dd>


<dt>print.scores</dt>
<dd>print the accuracy metrics.</dd>

</dl>

balancedaccuracy: Starovoitov-Golub Sine-Accuracy Function for Imbalanced Classification Data

Description

Usage

Value

Arguments

Author

Details

See Also

Examples