dials v0.0.9
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Tools for Creating Tuning Parameter Values
Many models contain tuning parameters (i.e. parameters that cannot be directly estimated from the data). These tools can be used to define objects for creating, simulating, or validating values for such parameters.
Readme
dials
Overview
This package contains tools to create and manage values of tuning
parameters and is designed to integrate well with the
parsnip package.
The name reflects the idea that tuning predictive models can be like turning a set of dials on a complex machine under duress.
Installation
You can install the released version of dials from CRAN with:
install.packages("dials")
You can install the development version from Github with:
devtools::install_github("tidymodels/dials")
Contributing
This project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
For questions and discussions about tidymodels packages, modeling, and machine learning, please post on RStudio Community.
If you think you have encountered a bug, please submit an issue.
Either way, learn how to create and share a reprex (a minimal, reproducible example), to clearly communicate about your code.
Check out further details on contributing guidelines for tidymodels packages and how to get help.
Functions in dials
| Name | Description | |
| cost | Support vector machine parameters | |
| all_neighbors | Parameter to determine which neighbors to use | |
| dials-package | dials: Tools for working with tuning parameters | |
| Laplace | Laplace correction parameter | |
| confidence_factor | Parameters for possible engine parameters for C5.0 | |
| degree | Parameters for exponents | |
| extrapolation | Parameters for possible engine parameters for Cubist | |
| activation | Activation functions between network layers | |
| Chicago | Chicago Ridership Data | |
| deg_free | Degrees of freedom (integer) | |
| max_num_terms | Parameters for possible engine parameters for earth models | |
| max_times | Word frequencies for removal | |
| learn_rate | Learning rate | |
| dist_power | Minkowski distance parameter | |
| grid_regular | Create grids of tuning parameters | |
| grid_max_entropy | Space-filling parameter grids | |
| finalize | Functions to finalize data-specific parameter ranges | |
| num_comp | Number of new features | |
| freq_cut | Near-zero variance parameters | |
| num_tokens | Parameter to determine number of tokens in ngram | |
| new-param | Tools for creating new parameter objects | |
| dropout | Neural network parameters | |
| mtry | Number of randomly sampled predictors | |
| encode_unit | Class for converting parameter values back and forth to the unit range | |
| neighbors | Number of neighbors | |
| predictor_prop | Proportion of predictors | |
| num_breaks | Number of cut-points for binning | |
| range_validate | Tools for working with parameter ranges | |
| mixture | Mixture of penalization terms | |
| min_unique | Number of unique values for pre-processing | |
| parameters_constr | Construct a new parameter set object | |
| over_ratio | Parameters for class-imbalance sampling | |
| parameters | Information on tuning parameters within an object | |
| regularization_factor | Parameters for possible engine parameters for ranger | |
| update.parameters | Update a single parameter in a parameter set | |
| unknown | Placeholder for unknown parameter values | |
| window_size | Parameter for the moving window size | |
| prune_method | MARS pruning methods | |
| penalty | Amount of regularization/penalization | |
| smoothness | Kernel Smoothness | |
| rbf_sigma | Kernel parameters | |
| surv_dist | Parametric distributions for censored data | |
| num_hash | Text hashing parameters | |
| weight_func | Kernel functions for distance weighting | |
| trees | Parameter functions related to tree- and rule-based models. | |
| max_tokens | Maximum number of retained tokens | |
| type_sum.param | Succinct summary of parameter objects | |
| pull_dials_object | Return a dials parameter object associated with parameters | |
| threshold | General thresholding parameter | |
| max_nodes | Parameters for possible engine parameters for randomForest | |
| min_dist | Parameter for the effective minimum distance between embedded points | |
| weight_scheme | Term frequency weighting methods | |
| value_validate | Tools for working with parameter values | |
| token | Token types | |
| weight | Parameter for "double normalization" when creating token counts | |
| No Results! | ||
Vignettes of dials
| Name | ||
| Basics.Rmd | ||
| No Results! | ||
Last month downloads
Details
| License | GPL-2 |
| URL | https://dials.tidymodels.org, https://github.com/tidymodels/dials |
| BugReports | https://github.com/tidymodels/dials/issues |
| Encoding | UTF-8 |
| LazyData | true |
| ByteCompile | true |
| RoxygenNote | 7.1.1 |
| VignetteBuilder | knitr |
| NeedsCompilation | no |
| Packaged | 2020-09-16 01:13:17 UTC; max |
| Repository | CRAN |
| Date/Publication | 2020-09-16 05:40:02 UTC |
| suggests | covr , kernlab , knitr , rmarkdown , rpart , testthat , xml2 |
| imports | DiceDesign , dplyr (>= 0.8.5) , glue , purrr , rlang , tibble , utils , vctrs (>= 0.3.0.9000) , withr |
| depends | R (>= 2.10) , scales |
| Contributors | RStudio |
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