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AllMetrics  

Calculating Multiple Performance Metrics of a Prediction Model
View on CRAN: Click here


Download and install AllMetrics package within the R console
Install from CRAN:
install.packages("AllMetrics")

Install from Github:
library("remotes")
install_github("cran/AllMetrics")

Install by package version:
library("remotes")
install_version("AllMetrics", "0.2.1")



Attach the package and use:
library("AllMetrics")
Maintained by
Dr. Sandip Garai
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-04-05
Latest Update: 2023-09-28
Description:
Provides a function to calculate multiple performance metrics for actual and predicted values. In total eight metrics will be calculated for particular actual and predicted series. Helps to describe a Statistical model's performance in predicting a data. Also helps to compare various models' performance. The metrics are Root Mean Squared Error (RMSE), Relative Root Mean Squared Error (RRMSE), Mean absolute Error (MAE), Mean absolute percentage error (MAPE), Mean Absolute Scaled Error (MASE), Nash-Sutcliffe Efficiency (NSE), Willmott
How to cite:
Dr. Sandip Garai (2023). AllMetrics: Calculating Multiple Performance Metrics of a Prediction Model. R package version 0.2.1, https://cran.r-project.org/web/packages/AllMetrics. Accessed 06 Nov. 2024.
Previous versions and publish date:
0.1.0 (2023-04-05 20:26), 0.1.1 (2023-04-22 02:53), 0.2.0 (2023-09-28 12:20)
Other packages that cited AllMetrics R package
View AllMetrics citation profile
Other R packages that AllMetrics depends, imports, suggests or enhances
Complete documentation for AllMetrics
Functions, R codes and Examples using the AllMetrics R package
Some associated functions: AllMetrics . 
Some associated R codes: AllMetrics.R .  Full AllMetrics package functions and examples
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