| artifact_path: outputs/mlflow-model |
| flavors: |
| python_function: |
| env: |
| conda: conda.yaml |
| virtualenv: python_env.yaml |
| loader_module: mlflow.sklearn |
| model_path: model.pkl |
| predict_fn: predict |
| python_version: 3.8.18 |
| sklearn: |
| code: null |
| pickled_model: model.pkl |
| serialization_format: pickle |
| sklearn_version: 1.0.2 |
| metadata: |
| azureml.base_image: mcr.microsoft.com/azureml/curated/azureml-automl:156 |
| azureml.engine: automl |
| mlflow_version: 2.9.2 |
| model_size_bytes: 328081 |
| model_uuid: 8bf40d2252604db19b915352dc348686 |
| run_id: ivory_coat_t5c6mdq773_2 |
| signature: |
| inputs: '[{"type": "string", "name": "Column2"}, {"type": "double", "name": "age"}, |
| {"type": "double", "name": "blood_pressure"}, {"type": "double", "name": "specific_gravity"}, |
| {"type": "double", "name": "albumin"}, {"type": "double", "name": "sugar"}, {"type": |
| "long", "name": "red_blood_cells"}, {"type": "long", "name": "pus_cell"}, {"type": |
| "long", "name": "pus_cell_clumps"}, {"type": "long", "name": "bacteria"}, {"type": |
| "double", "name": "blood_glucose_random"}, {"type": "double", "name": "blood_urea"}, |
| {"type": "double", "name": "serum_creatinine"}, {"type": "double", "name": "sodium"}, |
| {"type": "double", "name": "potassium"}, {"type": "double", "name": "haemoglobin"}, |
| {"type": "double", "name": "packed_cell_volume"}, {"type": "double", "name": "white_blood_cell_count"}, |
| {"type": "double", "name": "red_blood_cell_count"}, {"type": "long", "name": "hypertension"}, |
| {"type": "long", "name": "diabetes_mellitus"}, {"type": "long", "name": "coronary_artery_disease"}, |
| {"type": "long", "name": "appetite"}, {"type": "long", "name": "peda_edema"}, |
| {"type": "long", "name": "aanemia"}]' |
| outputs: '[{"type": "tensor", "tensor-spec": {"dtype": "int64", "shape": [-1]}}]' |
| params: null |
| utc_time_created: '2024-01-28 01:55:43.341930' |
|
|
