Package: kerasnip 0.2.0.9000

kerasnip: A Bridge Between 'keras' and 'tidymodels'

Provides a seamless bridge between 'keras' and the 'tidymodels' frameworks. It allows for the dynamic creation of 'parsnip' model specifications for 'keras' models.

Authors:David Díaz [aut, cph, cre]

kerasnip_0.2.0.9000.tar.gz
kerasnip_0.2.0.9000.zip(r-4.7-any)kerasnip_0.2.0.9000.zip(r-4.6-any)kerasnip_0.2.0.9000.zip(r-4.5-any)
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kerasnip_0.2.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
kerasnip/json (API)

# Install 'kerasnip' in R:
install.packages('kerasnip', repos = c('https://davidrsch.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/davidrsch/kerasnip/issues

Pkgdown/docs site:https://davidrsch.github.io

On CRAN:

Conda:

deep-learningdeep-learning-workflowkerasparsniptidymodels

5.20 score 12 stars 24 scripts 328 downloads 37 exports 90 dependencies

Last updated from:12e5b18a2e. Checks:7 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develWARNING194
source / vignettesOK235
linux-releaseWARNING180
macos-releaseWARNING253
macos-oldrelWARNING235
windows-develWARNING128
windows-releaseWARNING142
windows-oldrelWARNING115
wasm-releaseOK117

Exports:compile_keras_gridcreate_keras_functional_speccreate_keras_sequential_specextract_keras_historyextract_keras_modelextract_valid_gridgeneric_functional_fitgeneric_sequential_fitget_model_envinform_errorsinp_speckeras_evaluatekeras_losseskeras_metricskeras_optimizerskerasnip_add_tailorkerasnip_output_viewkerasnip_step_truthkerasnip_step_viewlaplace_conf_int_clslaplace_conf_int_reglaplace_pred_int_clslaplace_pred_int_regloss_function_kerasmodel_existsoptimizer_functionprocess_x_functionalprocess_x_sequentialprocess_y_functionalprocess_y_sequentialregister_keras_lossregister_keras_metricregister_keras_optimizerremove_keras_specstep_collapsestep_leadstep_sequence

Dependencies:abindbackportsbase64encclasscliclockcodetoolsconfigcpp11crayondata.tablediagramdigestdottydplyrfarverfastmapfuturefuture.applygenericsggplot2globalsgluegowergtablehardhathereipredisobandjsonlitekeras3KernSmoothlabelinglatticelavalifecyclelistenvlobstrlubridatemagrittrMASSMatrixnnetnumDerivparallellyparsnippillarpkgconfigpngprettyunitsprocessxprodlimprogressrpspurrrR6rappdirsRColorBrewerRcppRcppTOMLrecipesreticulaterlangrpartrprojrootrstudioapiS7scalesshapesparsevctrsSQUAREMstringistringrsurvivaltensorflowtfautographtfrunstibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewhiskerwithryamlzeallot

Readme and manuals

Help Manual

Help pageTopics
Butcher axe methods for kerasnip_model_fitaxe-kerasnip_model_fit axe_call.kerasnip_model_fit axe_ctrl.kerasnip_model_fit axe_data.kerasnip_model_fit axe_env.kerasnip_model_fit axe_fitted.kerasnip_model_fit
Compile Keras Models Over a Grid of Hyperparameterscompile_keras_grid
Create a Custom Keras Functional API Model Specification for Tidymodelscreate_keras_functional_spec
Create a Custom Keras Sequential Model Specification for Tidymodelscreate_keras_sequential_spec
Extract Keras Training Historyextract_keras_history
Extract Keras Model from a Fitted Kerasnip Objectextract_keras_model
Extract Valid Grid from Compilation Resultsextract_valid_grid
Inform About Compilation Errorsinform_errors
Remap Layer Block Arguments for Model Specificationinp_spec
Evaluate a Kerasnip Modelkeras_evaluate
Attach a 'tailor' Post-Processor to One Output or Step of a Multi-Output or Multistep Workflowkerasnip_add_tailor
View a Single Output of a Multi-Output kerasnip Fitkerasnip_output_view
Recover Truth Values for a Multistep Forecast Stepkerasnip_step_truth
View a Single Forecast Step of a Multistep kerasnip Fitkerasnip_step_view
Register a Custom Keras Lossregister_keras_loss
Register a Custom Keras Metricregister_keras_metric
Register a Custom Keras Optimizerregister_keras_optimizer
Remove a Keras Model Specification and its Registrationsremove_keras_spec
Collapse Predictors into a single list-columnstep_collapse
Create a Lead Predictorstep_lead
Build a Sliding Window of Predictors for Sequence Modelsstep_sequence