stacks - stacks 1.1.1

• A re-release of stacks 1.1.0 to address a note to resubmit following a since-resolved check failure.

Scientific Software - Peer-reviewed - R
Published by simonpcouch about 1 year ago

stacks - stacks 1.1.0

• Model stack and data stack print methods no longer raise conditions to print to the console (#228).

• Added missing commas and addressed formatting issues throughout the vignettes and articles. Backticks for package names were removed and missing parentheses for functions were added (@Joscelinrocha, #218).

• Increased the minimum R version to R 4.1.

• Transitioned support for parallel processing fully to the future framework. Parallelism backends registered with foreach will be ignored with a warning (#234).

Scientific Software - Peer-reviewed - R
Published by simonpcouch about 1 year ago

stacks - stacks 1.0.5

• Addressed inflation of butchered model stack object size after saving and reloading (#214).

• Fixed type-checking bug for add_candidates(name).

Scientific Software - Peer-reviewed - R
Published by simonpcouch almost 2 years ago

stacks - stacks 1.0.4

• Introduced support for parallel processing using the future framework. The stacks package previously supported parallelism with foreach, and users can use either framework for now. In a future release, stacks will begin the deprecation cycle for parallelism with foreach, so we encourage users to begin migrating their code now. See the Parallel Processing section in the tune package's "Optimizations" article to learn more (#866).

• Improved error message for unsupported model modes (#152).

Scientific Software - Peer-reviewed - R
Published by simonpcouch about 2 years ago

stacks - stacks 1.0.3

• Refine package alt text (#202).

• Update example objects, resolving deprecation warnings from recipes (#203).

• Fix bug in type checking for blend_predictions(mixture) (#204).

• Resolve package-level documentation aliasing notice from CRAN.

Scientific Software - Peer-reviewed - R
Published by simonpcouch over 2 years ago

stacks - stacks 1.0.2

• Added an augment() method for model_stack objects for compatibility with vetiver (#173).

• Converted all character variables in the tree_frogs example data to factor and updated downstream example objects (#177).

• Fixed bug that resulted in errors when using model formulas with the "mgcv" engine (#193).

• Made several optimizations to reduce evaluation time and memory allocation when stacking.

• Various bug fixes and improvements to documentation.

Scientific Software - Peer-reviewed - R
Published by simonpcouch about 3 years ago

stacks - stacks 1.0.1

• Tightened integration with the workflowsets package (#161, #165).

  • Refined logic with adding candidates via workflowsets to allow for partially trained workflow sets. In the case that a workflow set contains some failed tuning results, stacks will inform the user that they will be excluded from the data stack and only add the results that trained successfully.
  • Extended documentation related to the packages' interactions, including a new article on the package website.

• Revamped errors, warnings, and messages. Prompts now provide more thorough context about where they arose, include more extensive references to documentation, and are correctly pluralized (#150, #167).

• blend_predictions() doesn't error anymore if the control argument isn't a control_grid object. As long as the list passed to control include the same elements as control_grid() output, parsnip::condense_control() will handle input (#149).

• Removes an unneeded data import attribute from the tree_frogs example data and its associated objects (#148).

• Various bug fixes and improvements to documentation.

Scientific Software - Peer-reviewed - R
Published by simonpcouch over 3 years ago

stacks - stacks 1.0.0

stacks 1.0.0 is the first production release of the package. While this release includes only a few minor bug fixes, it's accompanied by a white paper recently published in the Journal of Open Source software. You can read that paper here!

This release:

• Addresses re-introduction of a bug arising from outcome levels that are not valid column names in the multinomial classification setting (#133).
• Fixes bug where stacks will return incorrect predictions if an elastic net meta-learner is used, the type argument to predict is set to "class", and the outcome levels differ from alphabetical order.
• Transitions package internals from functions deprecated from the recipes package.

Scientific Software - Peer-reviewed - R
Published by simonpcouch almost 4 years ago

stacks - stacks 0.2.4

This is a GitHub-only release and does not reflect CRAN source code. This update includes a data-raw/paper subdirectory containing source for a contributed paper to the Journal of Open Source Software.

Scientific Software - Peer-reviewed - R
Published by simonpcouch almost 4 years ago

stacks - stacks 0.2.3

While stacks 0.2.3 is a minor release, it includes a number of significant user experience improvements. This release adds an option to significantly reduce runtime for prediction blending, makes errors and warnings more informative, and greatly reduces the size of reloaded model objects in memory.

Regarding that first point, take a look at how adjusting the times argument in blend_predictions drastically affects its runtime:

```r library(tidymodels) library(modeldata)

using a version of the package where times is a param

library(stacks)

data("lending_club")

set.seed(1) lendingclub <- samplen(lending_club, 1000)

folds <- vfoldcv(lendingclub, v = 5)

lrmod <- linearreg(penalty = tune(), mixture = tune()) %>% setengine("glmnet") %>% workflow( preprocessor = fundedamnt ~ intrate + totalbalil, spec = . ) %>% tunegrid( resamples = folds, control = controlstackgrid(), grid = 10 )

system.time( stacks() %>% addcandidates(lrmod) %>% blend_predictions(times = 25) )

> user system elapsed

> 10.280 0.112 10.550

system.time( stacks() %>% addcandidates(lrmod) %>% blend_predictions(times = 10) )

> user system elapsed

> 4.424 0.050 4.554

system.time( stacks() %>% addcandidates(lrmod) %>% blend_predictions(times = 4) )

> user system elapsed

> 2.158 0.018 2.194

```

Related to the second point, there are several different degrees and varieties of tuning "failure" that result in stacks tripping up during model stacking. The package now inspects its inputs more closely and may give you a heads up when you might run into issues later on. Look out for warnings like:

```r

> Warning message:

> The inputted candidates argument my_tuning_results generated notes during tuning/resampling.

> Model stacking may fail due to these issues; see ?collect_notes if so.

```

And, finally, related to model stack object size, check out the the results of butcher::weigh on the results like the above reprex (after saving and reloading) before and after this release:

```r weigh(lrstackbefore)

> # A tibble: 374 × 2

> object size

>

> 1 coefs.preproc.terms 2.64

> 2 coefs.fit.call 2.64

> 3 coefs.spec.eng_args.lower.limits 2.64

> 4 coefs.spec.method.fit.args.lower.limits 2.64

> 5 coefs.spec.method.pred.numeric.post 1.76

> 6 memberfits.lrmod13.fit.fit.spec.method.pred.numeric.post 1.76

> 7 memberfits.lrmod11.fit.fit.spec.method.pred.numeric.post 1.76

> 8 memberfits.lrmod13.pre.actions.formula.blueprint.mold.process 0.0172

> 9 memberfits.lrmod13.pre.mold.blueprint.mold.process 0.0172

> 10 memberfits.lrmod11.pre.actions.formula.blueprint.mold.process 0.0172

> # … with 364 more rows

weigh(lrstackafter)

> # A tibble: 374 × 2

> object size

>

> 1 coefs.preproc.terms 24.7

> 2 coefs.fit.call 24.7

> 3 coefs.spec.eng_args.lower.limits 24.7

> 4 coefs.spec.method.fit.args.lower.limits 24.7

> 5 coefs.spec.method.pred.numeric.post 1.79

> 6 memberfits.lrmod13.fit.fit.spec.method.pred.numeric.post 1.79

> 7 memberfits.lrmod11.fit.fit.spec.method.pred.numeric.post 1.79

> 8 memberfits.lrmod13.pre.actions.formula.blueprint.mold.process 0.0172

> 9 memberfits.lrmod13.pre.mold.blueprint.mold.process 0.0172

> 10 memberfits.lrmod11.pre.actions.formula.blueprint.mold.process 0.0172

> # … with 364 more rows

```

Read more about these changes and their implementations at the issues linked below.🐧

Changelog

• Addressed deprecation warning in add_candidates (#99).
• Improved clarity of warnings/errors related to failed hyperparameter tuning and resample fitting (#110).
• Reduced model stack object size and fixed bug where object size of model stack inflated drastically after saving to file (#116). Also, regenerated example objects with this change--saved model objects may need to be regenerated in order to interface with newer versions of the package.
• Introduced a times argument to blend_predictions that is passed on to rsample::bootstraps when fitting stacking coefficients. Reducing this argument from its default (25) greatly reduces the run time of blend_predictions (#94).
• The package will now load packages necessary for model fitting at fit_members(), if available, and fail informatively if not (#118).
• Fixed bug where meta-learner tuning would fail with outcome names and levels including the string "class" (#125).
• The package will now warn when unused dots are passed to any of the core functions (#127).

Scientific Software - Peer-reviewed - R
Published by simonpcouch about 4 years ago

stacks - stacks 0.2.2

• Fixed errors arising from outcome levels that are not valid column names in the multinomial classification setting.
• Fixed collect_parameters failing to return stacking coefficients in the two-class classification setting.
• Regenerated example objects with updated {rsample} fingerprinting--saved model objects may need to be regenerated in order to build stacks combining models generated before and after this update.
• Various other bug fixes and improvements to documentation.

Scientific Software - Peer-reviewed - R
Published by simonpcouch over 4 years ago

stacks - stacks 0.2.1

• Updates for importing workflow sets that use the add_variables() preprocessor.
• Plot fixes for cases where coefficients are negative.
• Performance and member plots now show the effect of multiple mixture values.
• Package diagrams now have alt text.
• Various bug fixes and improvements to documentation.

Scientific Software - Peer-reviewed - R
Published by simonpcouch almost 5 years ago

stacks - stacks 0.2.0

This release integrates the package more closely with the tidymodels ecosystem, including support for finetune and workflowsets. It also introduces support for fitting ensembles with an elastic net and features a number of bug fixes and other improvements.

Breaking changes

This release of the package changes some elements of the internal structure of model stacks. As such, model stacks stored as saved objects will need to be regenerated before predicting, plotting, printing, etc.

New features

• The package now supports elastic net models as a meta-learner via the mixture argument to blend_predictions.
• The package can now add candidates from workflow_map objects from the new {workflowsets} package. The interface to add_candidates for doing so is the same as with tune_results objects, and add_candidates is now a generic function.
• Objects tuned with racing methods from the {finetune} package can now be added as candidate members.

Bug fixes

• Fixed bug in determining member hyperparameters during member fitting when using non-RMSE/ROC AUC metrics.
• Fixed bug arising from model definition names that are not valid column names. The package will now message in the case that the provided names are not valid column names and use make.names for associated candidate members.
  

Miscellaneous improvements

• Drop {digest} dependency in favor of {tune}/{rsample} "fingerprinting" to check consistency of resamples.
• fit_members() will now warn when supplied a model stack whose members have already been fitted.
• Integrate with {tune} functionality for appropriately coloring errors, warnings, and messages.
• Improved faceting and axis scales to make autoplot with type = "members" more informative.
• Various improvements to documentation.

Scientific Software - Peer-reviewed - R
Published by simonpcouch about 5 years ago

stacks - stacks 0.1.0

Initial release on CRAN!

Scientific Software - Peer-reviewed - R
Published by simonpcouch over 5 years ago