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parsnip 0.2.0

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@topepo topepo released this 09 Mar 13:07
v0.2.0
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Learn about vigilant mode.

Model Specification Changes

  • Bayesian additive regression trees (BART) were added via the bart() function.

  • Added the "glm" engine for linear_reg() for numeric outcomes (#624).

  • Added brulee engines for linear_reg(), logistic_reg(), multinom_reg() and mlp().

Bug fixes

  • A bug for class predictions of two-class GAM models was fixed (#541)

  • Fixed a bug for logistic_reg() with the LiblineaR engine (#552).

  • The list column produced when creating survival probability predictions is now always called .pred (with .pred_survival being used inside of the list column).

  • Fixed outcome type checking affecting a subset of regression models (#625).

  • New extract_parameter_set_dials() method to extract parameter sets from model specs.

  • New extract_parameter_dials() method to extract a single parameter from model specs.

  • Prediction using multinom_reg() with the nnet engine with a single row no longer fails (#612).

Other Changes

  • When the xy interface is used and the underlying model expects to use a matrix, a better warning is issued when predictors contain non-numeric columns (including dates).

  • The fit time is only calculated when the verbosity argument of control_parsnip() is 2L or greater. Also, the call to system.time() now uses gcFirst = FALSE. (#611)

  • fit_control() is soft-deprecated in favor of control_parsnip().

  • Argument interval was added for prediction: For types "survival" and "quantile", estimates for the confidence or prediction interval can be added if available (#615).

  • set_dependency() now allows developers to create package requirements that are specific to the model's mode (#604).

  • varying() is soft-deprecated in favor of tune().

  • varying_args() is soft-deprecated in favor of tune_args().

  • An autoplot() method was added for glmnet objects, showing the coefficient paths versus the penalty values (#642).

  • parsnip is now more robust working with keras and tensorflow for a larger range of versions (#596).

  • xgboost engines now use the new iterationrange parameter instead of the deprecated ntreelimit (#656).

Developer

  • Models information can be re-registered as long as the information being registered is the same. This is helpful for packages that add new engines and use devtools::load_all() (#653).
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