Tools for Creating Tuning Parameter Values


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Documentation for package ‘dials’ version 0.0.9

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A B C D E F G H I K L M N O P R S T U V W

-- A --

activation Activation functions between network layers
all_neighbors Parameter to determine which neighbors to use

-- B --

batch_size Neural network parameters

-- C --

Chicago Chicago Ridership Data
confidence_factor Parameters for possible engine parameters for C5.0
cost Support vector machine parameters
cost_complexity Parameter functions related to tree- and rule-based models.

-- D --

degree Parameters for exponents
degree_int Parameters for exponents
deg_free Degrees of freedom (integer)
dist_power Minkowski distance parameter
dropout Neural network parameters

-- E --

epochs Neural network parameters
extrapolation Parameters for possible engine parameters for Cubist

-- F --

finalize Functions to finalize data-specific parameter ranges
finalize.default Functions to finalize data-specific parameter ranges
finalize.list Functions to finalize data-specific parameter ranges
finalize.logical Functions to finalize data-specific parameter ranges
finalize.param Functions to finalize data-specific parameter ranges
finalize.parameters Functions to finalize data-specific parameter ranges
freq_cut Near-zero variance parameters
fuzzy_thresholding Parameters for possible engine parameters for C5.0

-- G --

get_batch_sizes Functions to finalize data-specific parameter ranges
get_log_p Functions to finalize data-specific parameter ranges
get_n Functions to finalize data-specific parameter ranges
get_n_frac Functions to finalize data-specific parameter ranges
get_n_frac_range Functions to finalize data-specific parameter ranges
get_p Functions to finalize data-specific parameter ranges
get_rbf_range Functions to finalize data-specific parameter ranges
grid_latin_hypercube Space-filling parameter grids
grid_latin_hypercube.list Space-filling parameter grids
grid_latin_hypercube.param Space-filling parameter grids
grid_latin_hypercube.parameters Space-filling parameter grids
grid_latin_hypercube.workflow Space-filling parameter grids
grid_max_entropy Space-filling parameter grids
grid_max_entropy.list Space-filling parameter grids
grid_max_entropy.param Space-filling parameter grids
grid_max_entropy.parameters Space-filling parameter grids
grid_max_entropy.workflow Space-filling parameter grids
grid_random Create grids of tuning parameters
grid_random.list Create grids of tuning parameters
grid_random.param Create grids of tuning parameters
grid_random.parameters Create grids of tuning parameters
grid_random.workflow Create grids of tuning parameters
grid_regular Create grids of tuning parameters
grid_regular.list Create grids of tuning parameters
grid_regular.param Create grids of tuning parameters
grid_regular.parameters Create grids of tuning parameters
grid_regular.workflow Create grids of tuning parameters

-- H --

has_unknowns Placeholder for unknown parameter values
hidden_units Neural network parameters

-- I --

is_unknown Placeholder for unknown parameter values

-- K --

kernel_offset Kernel parameters

-- L --

Laplace Laplace correction parameter
learn_rate Learning rate
loss_reduction Parameter functions related to tree- and rule-based models.
lower_quantile Parameters for possible engine parameters for ranger

-- M --

make_regular_grid Create grids of tuning parameters
max_nodes Parameters for possible engine parameters for randomForest
max_num_terms Parameters for possible engine parameters for earth models
max_rules Parameters for possible engine parameters for Cubist
max_times Word frequencies for removal
max_tokens Maximum number of retained tokens
min_dist Parameter for the effective minimum distance between embedded points
min_n Parameter functions related to tree- and rule-based models.
min_times Word frequencies for removal
min_unique Number of unique values for pre-processing
mixture Mixture of penalization terms
mtry Number of randomly sampled predictors
mtry_long Number of randomly sampled predictors

-- N --

neighbors Number of neighbors
new-param Tools for creating new parameter objects
new_qual_param Tools for creating new parameter objects
new_quant_param Tools for creating new parameter objects
no_global_pruning Parameters for possible engine parameters for C5.0
num_breaks Number of cut-points for binning
num_comp Number of new features
num_hash Text hashing parameters
num_random_splits Parameters for possible engine parameters for ranger
num_terms Number of new features
num_tokens Parameter to determine number of tokens in ngram

-- O --

over_ratio Parameters for class-imbalance sampling

-- P --

parameters Information on tuning parameters within an object
parameters.default Information on tuning parameters within an object
parameters.list Information on tuning parameters within an object
parameters.param Information on tuning parameters within an object
param_set Information on tuning parameters within an object
penalty Amount of regularization/penalization
predictor_prop Proportion of predictors
predictor_winnowing Parameters for possible engine parameters for C5.0
prod_degree Parameters for exponents
prune Parameter functions related to tree- and rule-based models.
prune_method MARS pruning methods
pull_dials_object Return a dials parameter object associated with parameters
pull_dials_object.model_spec Return a dials parameter object associated with parameters
pull_dials_object.parameters Return a dials parameter object associated with parameters
pull_dials_object.recipe Return a dials parameter object associated with parameters
pull_dials_object.workflow Return a dials parameter object associated with parameters

-- R --

ranger_class_rules Parameters for possible engine parameters for ranger
ranger_reg_rules Parameters for possible engine parameters for ranger
ranger_split_rules Parameters for possible engine parameters for ranger
range_get Tools for working with parameter ranges
range_set Tools for working with parameter ranges
range_validate Tools for working with parameter ranges
rbf_sigma Kernel parameters
regularization_factor Parameters for possible engine parameters for ranger
regularize_depth Parameters for possible engine parameters for ranger
rule_bands Parameters for possible engine parameters for C5.0

-- S --

sample_prop Parameter functions related to tree- and rule-based models.
sample_size Parameter functions related to tree- and rule-based models.
scale_factor Kernel parameters
signed_hash Text hashing parameters
significance_threshold Parameters for possible engine parameters for ranger
smoothness Kernel Smoothness
spline_degree Parameters for exponents
splitting_rule Parameters for possible engine parameters for ranger
stations Chicago Ridership Data
surv_dist Parametric distributions for censored data
svm_margin Support vector machine parameters

-- T --

threshold General thresholding parameter
token Token types
trees Parameter functions related to tree- and rule-based models.
tree_depth Parameter functions related to tree- and rule-based models.

-- U --

unbiased_rules Parameters for possible engine parameters for Cubist
under_ratio Parameters for class-imbalance sampling
unique_cut Near-zero variance parameters
unknown Placeholder for unknown parameter values
update.parameters Update a single parameter in a parameter set

-- V --

values_activation Activation functions between network layers
values_prune_method MARS pruning methods
values_surv_dist Parametric distributions for censored data
values_token Token types
values_weight_func Kernel functions for distance weighting
values_weight_scheme Term frequency weighting methods
value_inverse Tools for working with parameter values
value_sample Tools for working with parameter values
value_seq Tools for working with parameter values
value_set Tools for working with parameter values
value_transform Tools for working with parameter values
value_validate Tools for working with parameter values

-- W --

weight Parameter for '"double normalization"' when creating token counts
weight_func Kernel functions for distance weighting
weight_scheme Term frequency weighting methods
window_size Parameter for the moving window size