ba9eb3d7c7
- Made `date_column` a required field in `TrainModelParams`, ensuring it must be present in the input data. - Updated related documentation in `input-sample.md`, `README.md`, and various test scenarios to reflect the change in requirement. - Adjusted the handling of `date_format` to default to `yyyy-MM-dd HH:mm:ss` if omitted, enhancing usability. - Refined test scenarios to include new examples and ensure compliance with the updated parameter structure. These changes improve the robustness of the model training workflow and clarify the expectations for input data.
41 lines
1.0 KiB
JSON
41 lines
1.0 KiB
JSON
{
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"_description": "Naive Timestamp column header; snake_case date_column/date_format and training_data_timestamp_naive.csv.",
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"experiment_run_id": 1016,
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"variable_columns": [
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"303-WIT-200(Value)"
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],
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"target_variable": "03CV020/CORRENTE_N_M1_PV(Value)",
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"bucket_name": "model-training",
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"file_name": "training_data_timestamp_naive.csv",
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"line_separator": ",",
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"decimal_separator": ".",
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"date_column": "Timestamp",
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"date_format": "yyyy-MM-dd HH:mm:ss",
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"train_size": 80,
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"shuffle": true,
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"random_state": 42,
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"model_name": "Linear Regression",
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"model_type": "linear_regression",
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"data_model_kwargs": {
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"lag_train": {
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"303-WIT-200(Value)": 0
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},
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"lag_val": {
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"303-WIT-200(Value)": 0
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},
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"nan_treatment": "drop",
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"rem_static_win": false,
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"static_threshold": null,
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"start_date": null,
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"end_date": null,
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"support_filters": {},
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"removed_intervals": []
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},
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"model_kwargs": {
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"degree": 1,
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"interaction_only": false,
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"scaler_name": "None"
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},
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"opt_params": {}
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}
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