Quickstart: Tabular Regression with the command line interface#

NeurEco executable for Tabular models (Regression, Compression, Classification) is called NeurEcoDNN. It can be called directly from a terminal / powershell after a full installation of NeurEco.

To build a NeurEco Regression model, run the following command in the terminal:

neurecoDNN build path/to/build/configuration/file/build.conf

The skeleton of a configuration file required to build NeurEco Regression model, here build.conf, looks as follows (for the test case Energy consumption). Its fields should be filled according to the problem at hand.

{
        "neurecoDNN_build": {
                "DevSettings": {
                        "disconnect_inputs_if_possible": true,
                        "final_learning": true,
                        "initial_beta_reg": 0.1,
                        "parameter_number_limit": 0,
                        "valid_percentage": 33.33
                },
                "UserSettings": {
                        "gpu_id": 0,
                        "use_gpu": false
                },
                "build_compress": false,
                "checkpoint_address": "./EnergyConsumption/EnergyConsumption.checkpoint",
                "classification": false,
                "exc_filenames": [
                        "x_train.csv"
                ],
                "freeze_structure": false,
                "input_normalization": {
                        "normalize_per_feature": true,
                        "scale_type": "max_centered",
                        "shift_type": "min_centered"
                },
                "output_filenames": [
                        "y_train.csv"
                ],
                "output_normalization": {
                        "normalize_per_feature": true,
                        "scale_type": "auto",
                        "shift_type": "auto"
                },
                "resume": false,
                "starting_from_checkpoint_address": "",
                "start_build_from_model_number": -1,
                "test_exc_filenames": [
                        "x_test.csv"
                ],
                "test_output_filenames": [
                        "y_test.csv"
                ],
                "write_model_output_to_directory": "./EnergyConsumption/BuildingResults",
                "write_model_to": "./EnergyConsumption/EnergyConsumption.ednn"
        }
}

To perform an evaluation, run the following command in the terminal:

neurecoDNN evaluate path/to/evaluation/configuration/file/eval.conf

The skeleton of an evaluation configuration file, here eval.conf, looks as follows (for the test case Energy consumption). Its fields should be filled according to the problem at hand.

{
         "NeurEcoEvaluate": {
             "exc_filenames": [
                 "x_test.csv"
             ],
             "neureco_filename": "./EnergyConsumption/EnergyConsumption.ednn",
             "optional_output_reference": [
                 "y_test.csv"
             ],
             "write_model_output_to_directory": "./EvaluationResults"
         }
     }

Note

For detailed documentation on evaluate, see Evaluate NeurEco Regression model with the command line interface.

To export the model to the chosen format, run one of the following commands:

neurecoDNN exportC ./EnergyConsumption/EnergyConsumption.ednn ./EnergyConsumption.h double
neurecoDNN exportONNX ./EnergyConsumption/EnergyConsumption.ednn ./EnergyConsumption.onnx float16
neurecoDNN exportVBA ./EnergyConsumption/EnergyConsumption.ednn ./EnergyConsumption.onnx float
neurecoDNN exportFMU ./EnergyConsumption/EnergyConsumption.ednn ./EnergyConsumption.fmu

Export to these formats requires embed license.

Note

For detailed documentation on Tabular Regression with the command line interface, see Tabular Regression with the command line interface.