initial_umap() and target_weight() for recipes::step_umap() (#324).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).
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).
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).
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).
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.
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).
Chicago data set was removed. It can be found in the modeldata package.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().
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.
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.
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.
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.
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.
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.
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)
smoothness() was added.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.
offset() has been renamed kernel_offset() to avoid name conflicts.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.
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.
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.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.