Man pages for krzjoa/torchts
Time series Models with torch
| as_ts_dataloader | Quick shortcut to create a torch dataloader based on the... |
| as_ts_dataset | Create a torch dataset for time series data from a... |
| as.vector.torch_tensor | Convert 'torch_tensor' to a vector |
| call_optim | An auxilliary function to call optimizer |
| check_is_complete | Check if input data contains no NAs. Otherwise, return error. |
| check_is_new_data_complete | Check if new data has NAs in columns others than predicted... |
| check_recursion | Check, if recursion should be used in forecasting |
| clear_outcome | Partially clear outcome variable in new data by overriding... |
| col_map_out | Colmap for outcome variable |
| dict_size | Return size of categorical variables in the data.frame |
| embedding_size | Propose the length of embedding vector for each embedded... |
| fit_network | Fit a neural network |
| geometric_pyramid | Geometric pyramid rule |
| get_x | batch <- list(x_num = "aaa", x_cat = "bbb", y = "c")... |
| init_gate_bias | Initialize gates to pass full information |
| is_categorical | Check, if vector is categorical, i.e. if is logical, factor,... |
| lagged_mlp | General interface to MLP networks with lagged variables |
| make_lagged_mlp | torchts engine |
| make_rnn | torchts engine |
| model_mlp | A configurable feed forward network (Multi-Layer Perceptron)... |
| model_rnn | A configurable recurrent neural network model |
| nnf_mae | Mean absolute error |
| nnf_mape | Mean absolute percentage error |
| nnf_smape | Symmetric mean absolute percentage error |
| nn_mlp | A shortcut to create a feed-forward block (MLP block) |
| nn_multi_embedding | Create multiple embeddings at once |
| nn_nonlinear | Shortcut to create linear layer with nonlinear activation... |
| plot_forecast | Plot forecast vs ground truth |
| prepare_dl | Prepare dataloders |
| print_and_capture | https://stackoverflow.com/questions/26083625/how-do-you-include-data-frame-output-inside-warnings-and-errors |
| remove_model | Remove parsnip model For development purposes only |
| rep_if_one_element | Repeat element if it length == 1 |
| rnn | General interface to recurrent neural network models |
| rnn_output_size | RNN output size |
| set_device | Set model device. |
| tiny_m5 | A subset from M5 Walmart Challenge Dataset in one data frame |
| torchts_mlp | MLP model for time series forecasting |
| torchts_model | Torchts abstract model |
| torchts-package | torchts: Time Series Models in torch |
| torchts_palette | Picked from torchts logo |
| torchts_parse_formula | Parse time series formula |
| torchts_rnn | RNN model for time series forecasting |
| train_batch | Training helper |
| ts_dataset | Create a time series dataset from a 'torch_tensor' matrix |
| valid_batch | Validation helper function |
| weather_pl | Weather data from Polish "poles of extreme temperatures" in... |
| which_static | Check, which variables are static |
