Man pages for kindling
Higher-Level Interface of 'torch' Package to Auto-Train Neural Networks
| act_funs | Activation Functions Specification Helper |
| args | Activation Function Arguments Helper |
| dials-kindling | Tunable hyperparameters for 'kindling' models |
| dot-train_nn_tab_impl | Preprocessing bridge for data.frame and formula methods |
| early_stop | Early Stopping Specification |
| eval_act_funs | Activation Function Specs Evaluation |
| extract_depth_param | Extract depth parameter values from n_hlayer argument |
| ffnn_impl | FFNN Implementation |
| formula_to_expr_transformer | Convert Formula to Expression Transformer |
| formula_to_function | Formula to Function with Named Arguments |
| gen-nn-predict | Predict from a trained neural network |
| gen-nn-train | Generalized Neural Network Trainer |
| grid_depth | Depth-Aware Grid Generation for Neural Networks |
| kindling | '{kindling}': Higher-level interface of torch package to... |
| kindling-basemodels | Base models for Neural Network Training in kindling |
| kindling-nn-wrappers | kindling-tidymodels wrapper |
| kindling-varimp | Variable Importance Methods for kindling Models |
| layer-attributes | "Layer" attributes |
| layer_prs | Layer argument pronouns for formula-based specifications |
| make_kindling | Register kindling engines with parsnip |
| mlp_kindling | Multi-Layer Perceptron (Feedforward Neural Network) via... |
| new_act_fn | Custom Activation Function Constructor |
| nn_arch | Architecture specification for train_nn() |
| nn_gens | Functions to generate 'nn_module' (language) expression |
| nn_module_generator | Generalized Neural Network Module Expression Generator |
| ordinal_gen | Ordinal Suffixes Generator |
| predict-basemodel | Predict method for kindling basemodel fits |
| prepare_kindling_args | Prepare arguments for kindling models |
| print.ffnn_fit | Print method for ffnn_fit objects |
| print-layer_pronoun | Print method for the pronouns |
| print.nn_arch | Display 'nn_arch()' configuration |
| print.nn_fit | Print method for nn_fit objects |
| print.rnn_fit | Print method for rnn_fit objects |
| reexports | Objects exported from other packages |
| rnn_impl | RNN Implementation |
| rnn_kindling | Recurrent Neural Network via kindling |
| safe_sample | Safe sampling function |
| substitute_dot | Recursively Substitute . with Expression |
| table_summary | Summarize and Display a Two-Column Data Frame as a Formatted... |
| train_nn_impl | Shared core implementation |
| train_nn_impl_dataset | train_nn implementation for torch datasets |
| train_nnsnip | Parsnip Interface of 'train_nn()' |
| validate_device | Validate device and get default device |
