Man pages for dials
Tools for Creating Tuning Parameter Values

activationActivation functions between network layers
adjust_deg_freeParameters to adjust effective degrees of freedom
all_neighborsParameter to determine which neighbors to use
c5_parametersParameters for possible engine parameters for C5.0
ChicagoChicago Ridership Data
conditional_min_criterionParameters for possible engine parameters for party models
costSupport vector machine parameters
cubist_parametersParameters for possible engine parameters for Cubist
deg_freeDegrees of freedom (integer)
degreeParameters for exponents
dials-packagedials: Tools for working with tuning parameters
dist_powerMinkowski distance parameter
dropoutNeural network parameters
earth_parametersParameters for possible engine parameters for earth models
encode_unitClass for converting parameter values back and forth to the...
finalizeFunctions to finalize data-specific parameter ranges
freq_cutNear-zero variance parameters
grid_max_entropySpace-filling parameter grids
grid_regularCreate grids of tuning parameters
LaplaceLaplace correction parameter
learn_rateLearning rate
max_timesWord frequencies for removal
max_tokensMaximum number of retained tokens
min_distParameter for the effective minimum distance between embedded...
min_uniqueNumber of unique values for pre-processing
mixtureMixture of penalization terms
momentumGradient descent momentum parameter
mtryNumber of randomly sampled predictors
neighborsNumber of neighbors
new-paramTools for creating new parameter objects
num_breaksNumber of cut-points for binning
num_compNumber of new features
num_tokensParameter to determine number of tokens in ngram
over_ratioParameters for class-imbalance sampling
parametersInformation on tuning parameters within an object
parameters_constrConstruct a new parameter set object
penaltyAmount of regularization/penalization
predictor_propProportion of predictors
prior_slab_dispersionBayesian PCA parameters
prune_methodMARS pruning methods
pull_dials_objectReturn a dials parameter object associated with parameters
randomForest_parametersParameters for possible engine parameters for randomForest
ranger_parametersParameters for possible engine parameters for ranger
range_validateTools for working with parameter ranges
rbf_sigmaKernel parameters
regularization_methodEstimation methods for regularized models
select_featuresParameter to enable feature selection
shrinkage_correlationParameters for possible engine parameters for sda models
smoothnessKernel Smoothness
stop_iterEarly stopping parameter
surv_distParametric distributions for censored data
texthashText hashing parameters
thresholdGeneral thresholding parameter
tokenToken types
treesParameter functions related to tree- and rule-based models.
type_sum.paramSuccinct summary of parameter objects
unknownPlaceholder for unknown parameter values
update.parametersUpdate a single parameter in a parameter set
value_validateTools for working with parameter values
weightParameter for '"double normalization"' when creating token...
weight_funcKernel functions for distance weighting
weight_schemeTerm frequency weighting methods
window_sizeParameter for the moving window size
xgboost_parametersParameters for possible engine parameters for xgboost
dials documentation built on Sept. 10, 2021, 5:06 p.m.