JONATHAN ALEXANDER 7 months ago
commit 42709ccba9
161 changed files (0 B → 1.5 MiB)
  1. 11
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      mlruns/0/66f31f8f0939484581b5044c9802723b/artifacts/model/MLmodel
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      mlruns/0/66f31f8f0939484581b5044c9802723b/artifacts/model/conda.yaml
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      mlruns/0/66f31f8f0939484581b5044c9802723b/artifacts/model/requirements.txt
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mlruns/0/66f31f8f0939484581b5044c9802723b/artifacts/estimator.html (0 B → 4.8 KiB)

mlruns/0/66f31f8f0939484581b5044c9802723b/artifacts/final_model/MLmodel (0 B → 509 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/artifacts/final_model/conda.yaml (0 B → 250 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/artifacts/final_model/model.pkl (0 B → 731 KiB)

mlruns/0/66f31f8f0939484581b5044c9802723b/artifacts/final_model/python_env.yaml (0 B → 115 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/artifacts/final_model/requirements.txt (0 B → 124 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/artifacts/metric_info.json (0 B → 93 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/artifacts/model/MLmodel (0 B → 987 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/artifacts/model/conda.yaml (0 B → 250 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/artifacts/model/model.pkl (0 B → 731 KiB)

mlruns/0/66f31f8f0939484581b5044c9802723b/artifacts/model/python_env.yaml (0 B → 115 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/artifacts/model/requirements.txt (0 B → 124 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/artifacts/predictions.csv (0 B → 24 KiB)

mlruns/0/66f31f8f0939484581b5044c9802723b/inputs/21474a38f629246015dbc1a0f2a7908e/meta.yaml (0 B → 171 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/inputs/2cccf57a1bc8dff1d9edbf0ced5776a9/meta.yaml (0 B → 171 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/inputs/9319cda741352cf83c9bb42721320d90/meta.yaml (0 B → 170 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/meta.yaml (0 B → 453 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/metrics/RandomForestRegressor_score_X_test (0 B → 35 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/metrics/test_mean_absolute_error (0 B → 35 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/metrics/test_mean_squared_error (0 B → 34 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/metrics/test_r2_score (0 B → 35 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/metrics/test_root_mean_squared_error (0 B → 34 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/metrics/testing_score (0 B → 35 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/metrics/training_mean_absolute_error (0 B → 70 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/metrics/training_mean_squared_error (0 B → 69 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/metrics/training_r2_score (0 B → 70 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/metrics/training_root_mean_squared_error (0 B → 67 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/metrics/training_score (0 B → 70 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/bootstrap (0 B → 4 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/branch (0 B → 4 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/ccp_alpha (0 B → 3 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/criterion (0 B → 13 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/max_depth (0 B → 1 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/max_features (0 B → 1 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/max_leaf_nodes (0 B → 4 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/max_samples (0 B → 4 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/min_impurity_decrease (0 B → 3 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/min_samples_leaf (0 B → 1 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/min_samples_split (0 B → 1 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/min_weight_fraction_leaf (0 B → 3 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/n_estimators (0 B → 3 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/n_jobs (0 B → 4 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/oob_score (0 B → 5 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/random_state (0 B → 4 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/seed (0 B → 2 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/verbose (0 B → 1 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/params/warm_start (0 B → 5 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/tags/estimator_class (0 B → 46 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/tags/estimator_name (0 B → 21 B)

mlruns/0/66f31f8f0939484581b5044c9802723b/tags/mlflow.log-model.history (0 B → 2.7 KiB)

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