Fast Compact Multilayer Perceptrons
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Documentation for package ‘neuralnetwork’ version 0.1.0
Help Pages
| neuralnetwork-package | Compact neural networks for tabular R workflows |
| coef.neuralnetwork | Summarize neuralnetwork models |
| neuralnetwork | Compact neural networks for tabular R workflows |
| neuralnetwork-callbacks | Callbacks in neuralnetwork training |
| neuralnetwork-metrics | Metrics used by neuralnetwork |
| neuralnetwork-objects | neuralnetwork model objects |
| nn_class_ind | Compatibility helpers |
| nn_compute | Compatibility helpers |
| nn_confint | Compatibility helpers |
| nn_cv | Cross-validate neuralnetwork models |
| nn_evaluate | Evaluate a neuralnetwork model |
| nn_fit | Fit a small multilayer perceptron |
| nn_generalized_weights | Compatibility helpers |
| nn_gwplot | Compatibility helpers |
| nn_hessian | Compatibility helpers |
| nn_load | Save and load neuralnetwork models |
| nn_multinom | Compatibility helpers |
| nn_permutation_importance | Permutation feature importance |
| nn_save | Save and load neuralnetwork models |
| nn_tune | Tune neuralnetwork hyperparameters |
| nn_which_is_max | Compatibility helpers |
| plot.neuralnetwork | Plot neuralnetwork training loss |
| predict.neuralnetwork | Predict from a neuralnetwork model |
| print.neuralnetwork | Print a neuralnetwork model |
| summary.neuralnetwork | Summarize neuralnetwork models |