CRAN
MLmetrics 1.1.1
Machine Learning Evaluation Metrics
Released May 13, 2016 by Yachen Yan
This package is available for Renjin and there are no known compatibility issues.
Dependencies
A collection of evaluation metrics, including loss, score and utility functions, that measure regression, classification and ranking performance.
Installation
Maven
This package can be included as a dependency from a Java or Scala project by including
the following your project's pom.xml file.
Read more
about embedding Renjin in JVM-based projects.
<dependencies>
<dependency>
<groupId>org.renjin.cran</groupId>
<artifactId>MLmetrics</artifactId>
<version>1.1.1-b30</version>
</dependency>
</dependencies>
<repositories>
<repository>
<id>bedatadriven</id>
<name>bedatadriven public repo</name>
<url>https://nexus.bedatadriven.com/content/groups/public/</url>
</repository>
</repositories>
Renjin CLI
If you're using Renjin from the command line, you load this library by invoking:
library('org.renjin.cran:MLmetrics')
Test Results
This package was last tested against Renjin 0.9.2687 on Aug 25, 2018.
- AUC-examples
- Accuracy-examples
- Area_Under_Curve-examples
- ConfusionDF-examples
- ConfusionMatrix-examples
- F1_Score-examples
- FBeta_Score-examples
- GainAUC-examples
- Gini-examples
- KS_Stat-examples
- LiftAUC-examples
- LogLoss-examples
- MAE-examples
- MAPE-examples
- MSE-examples
- MedianAE-examples
- MedianAPE-examples
- MultiLogLoss-examples
- NormalizedGini-examples
- PRAUC-examples
- Poisson_LogLoss-examples
- Precision-examples
- R2_Score-examples
- RAE-examples
- RMSE-examples
- RMSLE-examples
- RMSPE-examples
- RRSE-examples
- Recall-examples
- Sensitivity-examples
- Specificity-examples
- ZeroOneLoss-examples