Package: parsnip 1.2.1.9003

Max Kuhn

parsnip: A Common API to Modeling and Analysis Functions

A common interface is provided to allow users to specify a model without having to remember the different argument names across different functions or computational engines (e.g. 'R', 'Spark', 'Stan', 'H2O', etc).

Authors:Max Kuhn [aut, cre], Davis Vaughan [aut], Emil Hvitfeldt [ctb], Posit Software, PBC [cph, fnd]

parsnip_1.2.1.9003.tar.gz
parsnip_1.2.1.9003.zip(r-4.5)parsnip_1.2.1.9003.zip(r-4.4)parsnip_1.2.1.9003.zip(r-4.3)
parsnip_1.2.1.9003.tgz(r-4.4-any)parsnip_1.2.1.9003.tgz(r-4.3-any)
parsnip_1.2.1.9003.tar.gz(r-4.5-noble)parsnip_1.2.1.9003.tar.gz(r-4.4-noble)
parsnip_1.2.1.9003.tgz(r-4.4-emscripten)parsnip_1.2.1.9003.tgz(r-4.3-emscripten)
parsnip.pdf |parsnip.html✨
parsnip/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/tidymodels/parsnip/issues

Datasets:

    On CRAN:

    16.21 score 597 stars 64 packages 3.1k scripts 32k downloads 2 mentions 180 exports 41 dependencies

    Last updated 14 days agofrom:a212f78f87. Checks:OK: 1 NOTE: 6. Indexed: yes.

    TargetResultDate
    Doc / VignettesOKNov 07 2024
    R-4.5-winNOTENov 07 2024
    R-4.5-linuxNOTENov 07 2024
    R-4.4-winNOTENov 07 2024
    R-4.4-macNOTENov 07 2024
    R-4.3-winNOTENov 07 2024
    R-4.3-macNOTENov 07 2024

    Exports:.censoring_weights_graf.check_glmnet_penalty_fit.check_glmnet_penalty_predict.cols.convert_form_to_xy_fit.convert_form_to_xy_new.convert_xy_to_form_fit.convert_xy_to_form_new.dat.extract_surv_status.extract_surv_time.facts.lvls.model_param_name_key.obs.organize_glmnet_pred.preds.x.y%>%add_rowindexaugmentauto_mlautoplotbag_marsbag_mlpbag_treebartboost_treeC5_rulesC5.0_traincase_weights_allowedcforest_traincheck_argscheck_empty_ellipsecheck_final_paramcondense_controlcontr_one_hotcontrol_parsnipconvert_stan_intervalctree_traincubist_rulesdbart_predict_calcdecision_treediscrim_flexiblediscrim_lineardiscrim_quaddiscrim_regularizedeval_argsextract_fit_engineextract_fit_timeextract_parameter_dialsextract_parameter_set_dialsextract_spec_parsnipfind_engine_filesfitfit_controlfit_xyfit_xy.model_specfit.model_specformat_classformat_classprobsformat_hazardformat_linear_predformat_numformat_survivalformat_timefrequency_weightsgen_additive_modget_dependencyget_encodingget_fitget_from_envget_model_envget_pred_typeglanceglm_groupedhas_multi_predictimportance_weightsis_varyingkeras_mlpkeras_predict_classesknit_engine_docslinear_reglist_md_problemslogistic_regmake_callmake_classesmake_engine_listmake_seealso_listmarsmatrix_to_quantile_predmax_mtry_formulamaybe_data_framemaybe_matrixmin_colsmin_rowsmlpmodel_printermulti_predictmulti_predict_argsmultinom_regnaive_Bayesnearest_neighbornew_model_specnull_modelnull_valuenullmodelparsnip_addinplspoisson_regpred_value_templatepredict_class.model_fitpredict_classprob.model_fitpredict_confintpredict_confint.model_fitpredict_hazard.model_fitpredict_linear_predpredict_linear_pred.model_fitpredict_numericpredict_numeric.model_fitpredict_predintpredict_predint.model_fitpredict_quantile.model_fitpredict_rawpredict_raw.model_fitpredict_survivalpredict_survival.model_fitpredict_timepredict_time.model_fitpredict.model_fitprepare_dataprint_model_specprompt_missing_implementationproportional_hazardsrand_forestrepair_callreq_pkgsrequired_pkgsrpart_trainrule_fitset_argsset_dependencyset_encodingset_engineset_env_valset_fitset_in_envset_modeset_model_argset_model_engineset_model_modeset_new_modelset_predset_tf_seedshow_callshow_enginesshow_fitshow_model_infospec_is_loadedspec_is_possiblestan_conf_intsurv_regsurvival_regsvm_linearsvm_polysvm_rbftidytranslatetranslate.defaulttuneupdate_dot_checkupdate_engine_parametersupdate_main_parametersupdate_model_info_fileupdate_specvaryingvarying_argsxgb_predictxgb_train

    Dependencies:clicodetoolscolorspacecpp11dplyrfansifarvergenericsggplot2globalsgluegtablehardhatisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigprettyunitspurrrR6RColorBrewerrlangscalessparsevctrsstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

    Introduction to parsnip

    Rendered fromparsnip.Rmdusingknitr::rmarkdownon Nov 07 2024.

    Last update: 2024-08-23
    Started: 2021-11-05

    Readme and manuals

    Help Manual

    Help pageTopics
    Extract survival status.extract_surv_status
    Extract survival time.extract_surv_time
    Add a column of row numbers to a data frameadd_rowindex
    Augment data with predictionsaugment.model_fit
    Automatic Machine Learningauto_ml
    Create a ggplot for a model objectautoplot.glmnet autoplot.model_fit
    Ensembles of MARS modelsbag_mars
    Ensembles of neural networksbag_mlp
    Ensembles of decision treesbag_tree
    Bayesian additive regression trees (BART)bart
    Boosted treesboost_tree
    C5.0 rule-based classification modelsC5_rules
    Using case weights with parsnipcase_weights
    Determine if case weights are usedcase_weights_allowed
    Contrast function for one-hot encodingscontr_one_hot
    Control the fit functioncontrol_parsnip
    A wrapper function for conditional inference tree modelscforest_train ctree_train
    Cubist rule-based regression modelscubist_rules
    Decision treesdecision_tree
    Data Set Characteristics Available when Fitting Models.cols .dat .facts .lvls .obs .preds .x .y descriptors
    Flexible discriminant analysisdiscrim_flexible
    Linear discriminant analysisdiscrim_linear
    Quadratic discriminant analysisdiscrim_quad
    Regularized discriminant analysisdiscrim_regularized
    Extract elements of a parsnip model objectextract-parsnip extract_fit_engine.model_fit extract_fit_time.model_fit extract_parameter_dials.model_spec extract_parameter_set_dials.model_spec extract_spec_parsnip.model_fit
    Fit a Model Specification to a Datasetfit.model_spec fit_xy.model_spec
    Generalized additive models (GAMs)gen_additive_mod
    Construct a single row summary "glance" of a model, fit, or other objectglance.model_fit
    Fit a grouped binomial outcome from a data set with case weightsglm_grouped
    Linear regressionlinear_reg
    Logistic regressionlogistic_reg
    Multivariate adaptive regression splines (MARS)mars
    Determine largest value of mtry from formula. This function potentially caps the value of 'mtry' based on a formula and data set. This is a safe approach for survival and/or multivariate models.max_mtry_formula
    Fuzzy conversionsmaybe_data_frame maybe_matrix
    Execution-time data dimension checksmin_cols min_rows
    Single layer neural networkmlp
    Model Fit Objectsmodel_fit
    Formulas with special terms in tidymodelsmodel_formula
    Model Specificationsmodel_spec
    Model predictions across many sub-modelsmulti_predict multi_predict.default multi_predict._C5.0 multi_predict._earth multi_predict._elnet multi_predict._glmnetfit multi_predict._lognet multi_predict._multnet multi_predict._torch_mlp multi_predict._train.kknn multi_predict._xgb.Booster
    Multinomial regressionmultinom_reg
    Naive Bayes modelsnaive_Bayes
    K-nearest neighborsnearest_neighbor
    Null modelnull_model
    Start an RStudio Addin that can write model specificationsparsnip_addin
    Partial least squares (PLS)pls
    Poisson regression modelspoisson_reg
    Random forestrand_forest
    Repair a model call objectrepair_call
    Determine required packages for a modelreq_pkgs
    Determine required packages for a modelrequired_pkgs.model_fit required_pkgs.model_spec
    RuleFit modelsrule_fit
    Change elements of a model specificationset_args set_mode set_mode.model_spec
    Declare a computational engine and specific argumentsset_engine
    Display currently available engines for a modelshow_engines
    Using sparse data with parsnipsparse_data
    Linear support vector machinessvm_linear
    Polynomial support vector machinessvm_poly
    Radial basis function support vector machinessvm_rbf
    Turn a parsnip model object into a tidy tibbletidy.model_fit
    Resolve a Model Specification for a Computational Enginetranslate translate.default
    Updating a model specificationparsnip_update update.bag_mars update.bag_mlp update.bag_tree update.bart update.boost_tree update.C5_rules update.cubist_rules update.decision_tree update.discrim_flexible update.discrim_linear update.discrim_quad update.discrim_regularized update.gen_additive_mod update.linear_reg update.logistic_reg update.mars update.mlp update.multinom_reg update.naive_Bayes update.nearest_neighbor update.pls update.poisson_reg update.proportional_hazards update.rand_forest update.rule_fit update.survival_reg update.surv_reg update.svm_linear update.svm_poly update.svm_rbf