Man pages for dials
Tools for Creating Tuning Parameter Values
| activation | Activation functions between network layers |
| adjust_deg_free | Parameters to adjust effective degrees of freedom |
| all_neighbors | Parameter to determine which neighbors to use |
| bart-param | Parameters for BART models These parameters are used for... |
| c5_parameters | Parameters for possible engine parameters for C5.0 |
| class_weights | Parameters for class weights for imbalanced problems |
| conditional_min_criterion | Parameters for possible engine parameters for partykit models |
| cost | Support vector machine parameters |
| cubist_parameters | Parameters for possible engine parameters for Cubist |
| deg_free | Degrees of freedom (integer) |
| degree | Parameters for exponents |
| dials-package | dials: Tools for working with tuning parameters |
| dist_power | Minkowski distance parameter |
| dropout | Neural network parameters |
| earth_parameters | Parameters for possible engine parameters for earth models |
| encode_unit | Class for converting parameter values back and forth to the... |
| finalize | Functions to finalize data-specific parameter ranges |
| freq_cut | Near-zero variance parameters |
| grid_max_entropy | Max-entropy and latin hypercube grids |
| grid_regular | Create grids of tuning parameters |
| grid_space_filling | Space-filling parameter grids |
| harmonic_frequency | Harmonic Frequency |
| initial_umap | Initialization method for UMAP |
| Laplace | Laplace correction parameter |
| learn_rate | Learning rate |
| lightgbm_parameters | Possible engine parameters for lightbgm |
| max_times | Word frequencies for removal |
| max_tokens | Maximum number of retained tokens |
| min_dist | Parameter for the effective minimum distance between embedded... |
| min_unique | Number of unique values for pre-processing |
| mixture | Mixture of penalization terms |
| momentum | Gradient descent momentum parameter |
| mtry | Number of randomly sampled predictors |
| mtry_prop | Proportion of Randomly Selected Predictors |
| neighbors | Number of neighbors |
| new-param | Tools for creating new parameter objects |
| num_breaks | Number of cut-points for binning |
| num_clusters | Number of Clusters |
| num_comp | Number of new features |
| num_knots | Number of knots (integer) |
| num_runs | Number of Computation Runs |
| num_tokens | Parameter to determine number of tokens in ngram |
| over_ratio | Parameters for class-imbalance sampling |
| parameters | Information on tuning parameters within an object |
| parameters_constr | Construct a new parameter set object |
| penalty | Amount of regularization/penalization |
| predictor_prop | Proportion of predictors |
| prior_slab_dispersion | Bayesian PCA parameters |
| prune_method | MARS pruning methods |
| randomForest_parameters | Parameters for possible engine parameters for randomForest |
| ranger_parameters | Parameters for possible engine parameters for ranger |
| range_validate | Tools for working with parameter ranges |
| rbf_sigma | Kernel parameters |
| reexports | Objects exported from other packages |
| regularization_method | Estimation methods for regularized models |
| scheduler-param | Parameters for neural network learning rate schedulers These... |
| select_features | Parameter to enable feature selection |
| shrinkage_correlation | Parameters for possible engine parameters for sda models |
| smoothness | Kernel Smoothness |
| stop_iter | Early stopping parameter |
| summary_stat | Rolling summary statistic for moving windows |
| surv_dist | Parametric distributions for censored data |
| survival_link | Survival Model Link Function |
| target_weight | Amount of supervision parameter |
| texthash | Text hashing parameters |
| threshold | General thresholding parameter |
| token | Token types |
| trees | Parameter functions related to tree- and rule-based models. |
| trim_amount | Amount of Trimming |
| type_sum.param | Succinct summary of parameter objects |
| unknown | Placeholder for unknown parameter values |
| update.parameters | Update a single parameter in a parameter set |
| validation_set_prop | Proportion of data used for validation |
| value_validate | Tools for working with parameter values |
| vocabulary_size | Number of tokens in vocabulary |
| weight | Parameter for '"double normalization"' when creating token... |
| weight_func | Kernel functions for distance weighting |
| weight_scheme | Term frequency weighting methods |
| window_size | Parameter for the moving window size |
| xgboost_parameters | Parameters for possible engine parameters for xgboost |
