Changes in version 1.4.3.9000 Changes in version 1.4.3 (2026-04-11) New parameters - ordinal_link() and odds_link() are two new parameters for the new ordinal_reg() models in parsnip (@corybrunson, #435). - num_estimators(), softmax_temperature(), balance_probabilities(), average_before_softmax(), and training_set_limit() are new parameters for the tab_pfn() model in parsnip (#412). Other changes - grid_space_filling() now also respects the original argument when pre-made designs are available (#409). - parameters() and the grid_*() functions give more information in the error message when non-parameter objects are passed in (#437, #438). - encode_unit() now provides a helpful error when x is not a parameter object (#430). - value_validate(), value_transform(), value_inverse(), and value_set() now produce more informative error messages when values contain unknowns (#445). - value_validate(), encode_unit(), get_p(), get_log_p(), get_n(), get_n_frac(), get_n_frac_range(), and get_batch_sizes() now enforce empty dots (#439). - Several further type-checking error messages now include the actual type of the input (#423). Changes in version 1.4.2 (2025-09-04) - prop_terms() is a new parameter object used for recipes that do supervised feature selection (#395). - upper_limit() and lower_limit() now have ranges that are inclusive of the endpoints, unless the endpoint is infinite (#396). - batch_size() now has a specific default parameter range instead of an unknown default range. get_batch_sizes() is deprecated (#398). Changes in version 1.4.1 (2025-07-29) - Two new parameters, cal_method_class() and cal_method_reg(), to control which method is used to calibrate model predictions (#383). - regularization_factor() is now exclusive of the lower border 0 in compliance with ranger::ranger() (#381). Changes in version 1.4.0 (2025-02-13) - For space-filling designs for $p$ parameters, there is a higher likelihood of finding a space-filling design for 1 < size <= p. Also, single-point designs now default to a random grid (#363). - value_seq() and value_sample() now respect the inclusive argument of quantitative parameters (#347). - The constructors, new_*_parameter(), now label unlabeled parameter (i.e., constructed with label = NULL) as such (#349). - All messages, warnings and errors has been translated to use {cli} package (#311). - parameters.list() now enforces the unused ellipsis to be empty (#378). - Added three new parameters for use in postprocessing in the tailor package (#357). - buffer() sets the distance on either side of a classification threshold within which predictions are considered equivocal in tailor::adjust_equivocal_zone(). - lower_limit() and upper_limit() sets the ranges for numeric predictions in tailor::adjust_numeric_range(). Breaking changes - The grid_*() functions now error instead of warn when provided with the wrong argument to control the grid size. So grid_space_filling(), grid_random(), grid_max_entropy(), and grid_latin_hypercube() now error if used with a levels argument and grid_regular() now errors if used with a size argument (#368). - The "optimal" option for the weight_func() parameter has been removed since it is choosing the optimal value based on the resubstition error (#370). - When constructing integer-valued parameters with a range of two consecutive values the inclusive argument needs to be set to c(TRUE, TRUE) to leave at least two values to sample from (#373). Changes in version 1.3.0 (2024-07-30) Improvements - The space-filling design functionality was expanded to include several new types of designs: Audze-Eglais, max/min L1, max/min L2, and uniform. These are all pre-computed designs accessed from the sfd package (#329). - A new function is used to access all of the space-filling designs called grid_space_filling() (#329). - Two new parameters, activation_2() and hidden_units_2(), for use with brulee::brulee_mlp_two_layer() (#339). Deprecations - grid_max_entropy() and grid_latin_hypercube() are deprecated in favor of grid_space_filling() (#332). - pull_dials_object() has been removed (#344). - The grid_*() methods for workflow objects have been removed (#344). - The deprecation of the default argument to the constructors new_quant_param() and new_qual_param() has been escalated to an error (#344). Changes in version 1.2.1 (2024-02-22) New parameters - Added initial_umap() and target_weight() for recipes::step_umap() (#324). Other changes - Improving styling of error messages by switching to cli (#315, #317, #321). - Update usage of tranformation functions from the scales package to their new names and require the corresponding version v1.3.0 (#323). Changes in version 1.2.0 (2023-04-03) New parameters - Added trim_amount() for recipes::step_impute_mean(). - Added num_runs() for recipes::step_nnmf() (#281). - Added harmonic_frequency() for recipes::step_harmonic() (#281). - Added validation_set_prop() for embed::step_discretize_xgb() (#280). Other changes - Deprecation of pull_dials_object() has been escalated to an error. Please use extract_parameter_dials() instead (#265). - The methods grid_regular.workflow(), grid_random.workflow(), grid_max_entropy.workflow(), and grid_latin_hypercube.workflow() have been deprecated (#302). - The constructor functions for single parameters, new_quant_param() and new_qual_param(), as well as for parameter sets, parameters_constr(), now have improved handling of the call shown in error messages (#291, #295). - The constructor for parameter sets, parameters_constr(), now checks that all inputs have the same length (#295). Changes in version 1.1.0 (2022-11-04) New parameters - Added learning rate scheduler parameters rate_decay(), rate_initial(), rate_largest(), rate_reduction(), rate_schedule(), rate_step_size(), and rate_steps() for the new brulee functions (#253). - Added num_clusters() parameter for tidyclust models (#259). - Added num_leaves() parameter for lightbgm models (@joeycouse, #256). Other changes - The default argument to the constructors new_quant_param() and new_qual_param() is deprecated. value_seq() now uses the same logic to generate a sequence of parameter values regardless of how long that sequence is (#153, #229). - prior_terminal_node_expo() for Bayesian adaptive regression trees (BART) now defaults to a range greater than 1 to limit explosive tree growth (#251). - The label for spline_degree() was improved. Changes in version 1.0.0 (2022-06-14) - The new parameter mtry_prop() is a variation on mtry() where the value is interpreted as the proportion (rather than the count) of predictors that will be randomly sampled at each split (#233). - conditional_test_statistic() and conditional_test_type() now work with the partykit engine rather than the party engine (#224). - new_quant_param() no longer requires range and inclusive if values is supplied (#87). Changes in version 0.1.1 (2022-04-06) - The Chicago data set was removed. It can be found in the modeldata package. Changes in version 0.1.0 (2022-01-31) New parameters - summary_stat() is a new parameter for use in recipes::step_window(). - A general class_weights() parameter was added for imbalanced models. - prior_outcome_range(), prior_terminal_node_coef(), and prior_terminal_node_expo() are new parameters for prior distribution specification related to parsnip::bart(). - num_knots() and survival_link() are new parameters for spline survival models (@mattwarkentin, #195). - vocabulary_size() is a new parameter used in textrecipes::step_tokenize_sentencepiece() and textrecipes::step_tokenize_bpe(). Other changes - The new extract_parameter_dials() method supersedes pull_dials_object() which has been deprecated. - activation() now supports values of "tanh". - New link to article explaining how to make custom parameter objects was added to the pkgdown site. Changes in version 0.0.10 (2021-09-10) New parameters - adjust_deg_free() and select_features() for generalized additive models. - conditional_min_criterion, conditional_test_statistic, conditional_test_type for models with the party engine. - diagonal_covariance(), regularization_method(), shrinkage_correlation(), shrinkage_frequencies(), and shrinkage_variance() for linear and quadratic discriminant analysis. - penalty_L1(), penalty_L2(), and scale_pos_weight() for boosted trees with the xgboost engine (@joeycouse, #176). - prior_mixture_threshold() and prior_slab_dispersion() for sparse PCA. - stop_iter() for early stopping. Other changes - Re-licensed package from GPL-2 to MIT. See consent from copyright holders here. - param_set(), scheduled for removal in version 0.0.5, is now removed. Changes in version 0.0.9 (2020-09-16) - Quantitative parameters now print the number of possible values if they have been set with value_set() (@kmdupr33, #138). - The print() method for parameters() has changed to be more clear. - A new function, pull_dials_object() was also added. - Duplicate parameter combinations are now automatically removed from grid results. - The range for epochs() was change to start at 10 iterations instead of 1. - The lower range for spline_degree() now starts at 1 instead of 3. - The upper range for cost() now goes to 2^5 instead of 2^-1. Changes in version 0.0.8 (2020-07-08) - A number of new parameter objects associated with engine-specific functions were added for engines "ranger", "randomForest", "earth" and "C5.0". Changes in version 0.0.7 (2020-06-10) - The grid_*() functions no longer generate subclassed tibbles. - predictor_prop() was added. - The levels argument for tune_grid() can now handle a named vector, to account for differences in ordering. Breaking changes - The range of dist_power() was changed so that the lower limit is 1. - The deprecation period for margin() is over; please use svm_margin() instead. Changes in version 0.0.6 (2020-04-03) - Quick bug fix release related to range checks in 0.0.5. The check is more forgiving when the required type is integer and a double is provided. Changes in version 0.0.5 (2020-04-01) - When kept in the original units, a parameter's range must now be the same data type as the parameter. - Renamed margin() to svm_margin() (@gabrielodom and @gralgomez, #85) - A bug in space filling designs with qualitative parameters was fixed (#94) - A better error message was created when grids are used with parameters sets that contain parameters that require finalization (#99) - Space-filling desings now share the same attributes as other grid objects (#100) - The range for sample_frac() was fixed (#96) Changes in version 0.0.4 (2019-12-02) New parameter functions: - Parameters smoothness() was added. Other changes - param_set() is being renamed parameters(). The old name implied that you only use it to set parameters (say from a recipe or model rather than de novo). param_set() will be available until version 0.0.5. - The range for num_hash() was increase to be 2^8 to 2^12. - The range for max_tokens() was changed to be 0 to 1000. Breaking changes - offset() has been renamed kernel_offset() to avoid name conflicts. Changes in version 0.0.3 (2019-10-01) Breaking changes - All parameter objects are now parameter functions. For example, the pre-configured object mtry is now a function, mtry(), with arguments for the range and the trans. This provides greater flexibility in parameter creation, and should feel more natural. - deg_free() erroneously produced real values; integers are now returned. - Default ranges were changed for learn_rate() and neighbors() were changed. - update.param_set() now takes multiple named arguments. Other changes - Two functions for space-filling designs were added: grid_max_entropy() and grid_latin_hypercube(). - A data set was added for modeling ridership on the Chicago L trains. New parameter functions: - Parameters spline_degree(), over_ratio(), under_ratio(), freq_cut(), unique_cut(), num_breaks(), min_unique(), num_hash(), signed_hash(), sample_prop(), window_size(), min_dist(), and degree_int() were added. Changes in version 0.0.2 (2018-12-09) - Parameter objects now contain code to finalize their values and a number of helper functions for certain data-specific parameters. A force option can be used to avoid updating the values. - Parameter objects are printed differently inside of tibbles. - regularization was changed to penalty in a few models to be consistent with this change. - batch_size and threshold were added. - Added a set of parameters for the textrecipes package issue 16. Changes in version 0.0.1 (2018-08-13) - First CRAN version