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_to": "./EnergyConsumption/EnergyConsumption.ednn"
        }
}

Note

For detailed documentation on build, see Build NeurEco Regression model with the command line interface. For data preparation, see Data preparation for NeurEco Regression with the command line interface.

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.