vitor-aignosi
10c7e292b9
Refactor ModelMetrics to utilize DriftAnalysis for drift detection - Replaced ModelAnalysis with DriftAnalysis in the ModelMetrics class to enhance drift detection capabilities. - Updated method signatures and documentation to reflect the changes in target_name and return values. - Adjusted data handling to ensure compatibility with the new analysis methods and improved clarity in the drift metrics dataframe preparation.
46 lines
1.1 KiB
JSON
46 lines
1.1 KiB
JSON
{
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"metadata": {
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"metadata": {
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"model_id": "{{MODEL_ID}}",
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"model_name": "test_model",
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"schedule_name": "test-schedule",
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"workflow_name": "predictions_batch"
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}
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},
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"schedule_name": "test-schedule",
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"model_name": "test_model",
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"model_id": "{{MODEL_ID}}",
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"query": "SELECT timestamp, variable, value, created_at FROM sientia_data.laborious_data WHERE model_id = {{MODEL_ID}}",
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"schema": "sientia_data",
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"table_name": "predictions",
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"transform_table_name": "transformed_data",
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"input_filters": {
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"EMPTY_DATA": {
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"POLICY": "STOP",
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"CONFIG": {}
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}
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},
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"mlflow_transform_filters": {
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"API_ERROR": {
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"POLICY": "STOP",
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"CONFIG": {}
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}
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},
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"mlflow_predict_filters": {
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"API_ERROR": {
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"POLICY": "STOP",
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"CONFIG": {}
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}
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},
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"path_priority": ["STOP", "CONTINUE", "REPEAT"],
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"opc_output_config": {},
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"pi_web_api_output_config": {},
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"save_transform": true,
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"prediction_store_policy": "lts:1",
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"model_config": {
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"target": "sensor_1",
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"retention_minutes": 0
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},
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"datetime_columns": ["timestamp", "created_at"]
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}
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