README.md
In nikitagusarov/performancer: Performance Metrics for Discrete Choice Analysis
Performance Metrics for Discrete Choice Analysis
The package performancer provides a number of function to easily calculate many of the performance metrics used in classification and discrete choice analysis tasks.
The main theoretical reference for this implementation is the handbook "Evaluating Learning Algorithms : A Classification Perspective" by Nathalie Japkowicz and Mohak Shah (Cambridge University Press 2011)
Installation
To install the package directly from GitHub run:
devtools::install_github("nikitagusarov/performancer")
Developpement
For more information, do not hesitate to contact me at nikita.gusarov@univ-grenoble-alpes.fr.
nikitagusarov/performancer documentation built on Jan. 12, 2023, 12:19 a.m.
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Performance Metrics for Discrete Choice Analysis
The package performancer provides a number of function to easily calculate many of the performance metrics used in classification and discrete choice analysis tasks.
The main theoretical reference for this implementation is the handbook "Evaluating Learning Algorithms : A Classification Perspective" by Nathalie Japkowicz and Mohak Shah (Cambridge University Press 2011)
Installation
To install the package directly from GitHub run:
devtools::install_github("nikitagusarov/performancer")
Developpement
For more information, do not hesitate to contact me at nikita.gusarov@univ-grenoble-alpes.fr.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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