CRAN
Metrics 0.1.4
Evaluation Metrics for Machine Learning
Released Jul 9, 2018 by Michael Frasco
An implementation of evaluation metrics in R that are commonly used in supervised machine learning. It implements metrics for regression, time series, binary classification, classification, and information retrieval problems. It has zero dependencies and a consistent, simple interface for all functions.
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>Metrics</artifactId> <version>0.1.4-b1</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:Metrics')
Test Results
This package was last tested against Renjin 0.9.2657 on Aug 18, 2018.
- Classification_metrics.classification_error_is_calculated_correctly_E1
- Classification_metrics.classification_error_is_calculated_correctly_E2
- Classification_metrics.classification_error_is_calculated_correctly_E3
- Classification_metrics.classification_error_is_calculated_correctly_E4
- Classification_metrics.classification_error_is_calculated_correctly_E5
- Classification_metrics.mean_quadratic_weighted_kappa_is_calculated_correctly_E1
- Classification_metrics.mean_quadratic_weighted_kappa_is_calculated_correctly_E2
- Classification_metrics.mean_quadratic_weighted_kappa_is_calculated_correctly_E3
- Classification_metrics.quadratic_weighted_kappa_is_calculated_correctly_E1
- Classification_metrics.quadratic_weighted_kappa_is_calculated_correctly_E2
- Classification_metrics.quadratic_weighted_kappa_is_calculated_correctly_E3
- Classification_metrics.quadratic_weighted_kappa_is_calculated_correctly_E4
- Classification_metrics.quadratic_weighted_kappa_is_calculated_correctly_E5
- Information_Retrieval.average_precision_at_k_is_calculated_correctly_E1
- Information_Retrieval.average_precision_at_k_is_calculated_correctly_E2
- Information_Retrieval.average_precision_at_k_is_calculated_correctly_E3
- Information_Retrieval.average_precision_at_k_is_calculated_correctly_E4
- Information_Retrieval.average_precision_at_k_is_calculated_correctly_E5
- Information_Retrieval.average_precision_at_k_is_calculated_correctly_E6
- Information_Retrieval.f1_score_is_calculated_correctly_E1
- Information_Retrieval.f1_score_is_calculated_correctly_E2
- Information_Retrieval.f1_score_is_calculated_correctly_E3
- Information_Retrieval.mean_average_precision_at_k_is_calculated_correctly_E1
- Information_Retrieval.mean_average_precision_at_k_is_calculated_correctly_E2
- Information_Retrieval.mean_average_precision_at_k_is_calculated_correctly_E3
- Information_Retrieval.mean_average_precision_at_k_is_calculated_correctly_E4
- Information_Retrieval.mean_average_precision_at_k_is_calculated_correctly_E5
- MeanQuadraticWeightedKappa-examples
- Regression_metrics_.absolute_error_is_calculated_correctly_E1
- Regression_metrics_.absolute_error_is_calculated_correctly_E2
- Regression_metrics_.absolute_percent_error_is_calculated_correctly_E1
- Regression_metrics_.absolute_percent_error_is_calculated_correctly_E2
- Regression_metrics_.absolute_percent_error_is_calculated_correctly_E3
- Regression_metrics_.bias_is_calculated_correctly_E1
- Regression_metrics_.bias_is_calculated_correctly_E2
- Regression_metrics_.mean_absolute_error_is_calculated_correctly
- Regression_metrics_.mean_absolute_percent_error_is_calculated_correctly_E1
- Regression_metrics_.mean_absolute_percent_error_is_calculated_correctly_E2
- Regression_metrics_.mean_squared_error_is_calculated_correctly
- Regression_metrics_.mean_squared_log_error_is_calculated_correctly
- Regression_metrics_.median_absolute_error_is_calculated_correctly
- Regression_metrics_.percent_bias_is_calculated_correctly_E1
- Regression_metrics_.percent_bias_is_calculated_correctly_E2
- Regression_metrics_.percent_bias_is_calculated_correctly_E3
- Regression_metrics_.percent_bias_is_calculated_correctly_E4
- Regression_metrics_.relative_absolute_error_is_calculated_correctly_E1
- Regression_metrics_.relative_absolute_error_is_calculated_correctly_E2
- Regression_metrics_.relative_absolute_error_is_calculated_correctly_E3
- Regression_metrics_.relative_squared_error_is_calculated_correctly_E1
- Regression_metrics_.relative_squared_error_is_calculated_correctly_E2
- Regression_metrics_.relative_squared_error_is_calculated_correctly_E3
- Regression_metrics_.root_mean_squared_error_is_calculated_correctly_E1
- Regression_metrics_.root_mean_squared_error_is_calculated_correctly_E2
- Regression_metrics_.root_mean_squared_log_error_is_calculated_correctly
- Regression_metrics_.root_relative_squared_error_is_calculated_correctly_E1
- Regression_metrics_.root_relative_squared_error_is_calculated_correctly_E2
- Regression_metrics_.root_relative_squared_error_is_calculated_correctly_E3
- Regression_metrics_.squared_error_is_calculated_correctly_E1
- Regression_metrics_.squared_error_is_calculated_correctly_E2
- Regression_metrics_.squared_log_error_is_calculated_correctly_E1
- Regression_metrics_.squared_log_error_is_calculated_correctly_E2
- Regression_metrics_.sum_of_squared_errors_is_calculated_correctly
- Regression_metrics_.symmetric_mean_absolute_percent_error_is_calculated_correctly_E1
- Regression_metrics_.symmetric_mean_absolute_percent_error_is_calculated_correctly_E2
- Regression_metrics_.symmetric_mean_absolute_percent_error_is_calculated_correctly_E3
- Regression_metrics_.symmetric_mean_absolute_percent_error_is_calculated_correctly_E4
- ScoreQuadraticWeightedKappa-examples
- Time_series_metrics_.mean_absolute_scaled_error_is_computed_correctly_E1
- Time_series_metrics_.mean_absolute_scaled_error_is_computed_correctly_E2
- accuracy-examples
- ae-examples
- ape-examples
- apk-examples
- auc-examples
- bias-examples
- binary_classification.area_under_ROC_curve_is_calculated_correctly_E1
- binary_classification.area_under_ROC_curve_is_calculated_correctly_E2
- binary_classification.area_under_ROC_curve_is_calculated_correctly_E3
- binary_classification.area_under_ROC_curve_is_calculated_correctly_E4
- binary_classification.f-beta_score_is_calculated_correctly_E1
- binary_classification.f-beta_score_is_calculated_correctly_E2
- binary_classification.f-beta_score_is_calculated_correctly_E3
- binary_classification.f-beta_score_is_calculated_correctly_E4
- binary_classification.log_loss_is_calculated_correctly_E1
- binary_classification.log_loss_is_calculated_correctly_E2
- binary_classification.log_loss_is_calculated_correctly_E3
- binary_classification.log_loss_is_calculated_correctly_E4
- binary_classification.mean_los_loss_is_calculated_correctly_E1
- binary_classification.mean_los_loss_is_calculated_correctly_E2
- binary_classification.mean_los_loss_is_calculated_correctly_E3
- binary_classification.precision_is_calculated_correctly_E1
- binary_classification.precision_is_calculated_correctly_E2
- binary_classification.precision_is_calculated_correctly_E3
- binary_classification.recall_is_calculated_correctly_E1
- binary_classification.recall_is_calculated_correctly_E2
- binary_classification.recall_is_calculated_correctly_E3
- ce-examples
- f1-examples
- fbeta_score-examples
- ll-examples
- logLoss-examples
- mae-examples
- mape-examples
- mapk-examples
- mase-examples
- mdae-examples
- mse-examples
- msle-examples
- percent_bias-examples
- precision-examples
- rae-examples
- recall-examples
- rmse-examples
- rmsle-examples
- rrse-examples
- rse-examples
- se-examples
- sle-examples
- smape-examples
- sse-examples
- testthat