NEWS (original) (raw)
MetricsWeighted 1.0.4
Minor improvements
- Better code formatting.
- More return() statements.
- Speed-up for some regression metrics.
- Push code coverage version.
MetricsWeighted 1.0.3
Improvements
logLoss()anddeviance_poisson()are now less picky about predictions of 0 (or 1).
MetricsWeighted 1.0.2
Documentation
- Fix Latex problem in MacOS help files.
- Slight improvements in docu.
MetricsWeighted 1.0.1
Documentation
- Much more compact help files
- Using Latex in help files
MetricsWeighted 1.0.0
This release bumps the package to stable version 1.0.0.
Maintenance
- Reorganization of code
- Switch to
package::function()notation
MetricsWeighted 0.5.5
Maintenance
- Use github workflows
- Add github pages
- Better README
Dependencies
- Removed {dplyr} from suggested packages.
MetricsWeighted 0.5.4
This is a maintainance update without any code change.
- Fixed problematic unit tests.
- Internal restructuring how package content is being generated.
MetricsWeighted 0.5.3
- Added unit tests
- Added option
reference_meantor_squared()functions. This allows clean out-of-sample applications. - Added Murphy diagrams
MetricsWeighted 0.5.2
Maintainance release. rmarkdown is now an explicit “Suggested” package.
MetricsWeighted 0.5.1
New function
weighted_corto calculate weighted correlation between actual and observed values.prop_withinto calculate weighted proportion of predictions within a tolerance around actual values.
Requirements
- Reduced minimal R version from 3.5 to 3.1.
Documentation
- Clarified that R-squared is calculated with respect to the null model calculated from the actual values.
MetricsWeighted 0.5.0
New functions
- Elementary scoring functions for expectiles and quantiles.
multi_metric: A way to create a named list of performance measures parametrized by a parameter.
MetricsWeighted 0.4.0
New functions
Added the following convenience wrappers tor_squared.
r_squared_poissonr_squared_gammar_squared_bernoulli
MetricsWeighted 0.3.0
New function
Added function weighted_var to calculate variance weighted by sampling weights.
MetricsWeighted 0.2.0
- Improvement of documentation and examples.
- Better handling of Tweedie special cases.
- More strict error handling.
- Added median absolute error (and weighted_median, weighted_quantile)
MetricsWeighted 0.1.0
Initial release.