| Name : R-wconf
| |
| Version : 1.2.0
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp156.1.1
| Date : 2024-09-10 01:36:41
|
| Group : Development/Libraries/Other
| Source RPM : R-wconf-1.2.0-lp156.1.1.src.rpm
|
| Size : 0.15 MB
| |
| Packager : https://www_suse_com/
| |
| Summary : Weighted Confusion Matrix
|
Description :
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>.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/15.6/x86_64 |
