joshcr25 commited on
Commit
46fb371
·
verified ·
1 Parent(s): 7b587fa

Upload 240 files

Browse files
This view is limited to 50 files because it contains too many changes.   See raw diff
Files changed (50) hide show
  1. m-0e36dc876e784ecbaa8a9404a6461f1d/artifacts/MLmodel +19 -0
  2. m-0e36dc876e784ecbaa8a9404a6461f1d/artifacts/conda.yaml +12 -0
  3. m-0e36dc876e784ecbaa8a9404a6461f1d/artifacts/python_env.yaml +7 -0
  4. m-0e36dc876e784ecbaa8a9404a6461f1d/artifacts/python_model.pkl +3 -0
  5. m-0e36dc876e784ecbaa8a9404a6461f1d/artifacts/requirements.txt +5 -0
  6. m-0e36dc876e784ecbaa8a9404a6461f1d/meta.yaml +10 -0
  7. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Bogor +1 -0
  8. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Bojong Gede +1 -0
  9. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Cawang +1 -0
  10. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Cikini +1 -0
  11. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Cilebut +1 -0
  12. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Citayam +1 -0
  13. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Depok +1 -0
  14. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Depok Baru +1 -0
  15. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Duren Kalibata +1 -0
  16. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Gondangdia +1 -0
  17. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Jakarta Kota +1 -0
  18. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Jayakarta +1 -0
  19. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Juanda +1 -0
  20. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Lenteng Agung +1 -0
  21. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Mangga Besar +1 -0
  22. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Manggarai +1 -0
  23. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Pasar Minggu +1 -0
  24. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Pasar Minggu Baru +1 -0
  25. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Pondok Cina +1 -0
  26. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Sawah Besar +1 -0
  27. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Tanjung Barat +1 -0
  28. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Tebet +1 -0
  29. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Universitas Indonesia +1 -0
  30. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Universitas Pancasila +1 -0
  31. m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/confidence +1 -0
  32. m-0e36dc876e784ecbaa8a9404a6461f1d/params/route +1 -0
  33. m-0e36dc876e784ecbaa8a9404a6461f1d/params/time +1 -0
  34. m-0e36dc876e784ecbaa8a9404a6461f1d/params/train_id +1 -0
  35. m-0e36dc876e784ecbaa8a9404a6461f1d/tags/mlflow.modelVersions +1 -0
  36. m-0e36dc876e784ecbaa8a9404a6461f1d/tags/mlflow.note.content +1 -0
  37. m-0e36dc876e784ecbaa8a9404a6461f1d/tags/mlflow.source.git.commit +1 -0
  38. m-0e36dc876e784ecbaa8a9404a6461f1d/tags/mlflow.source.name +1 -0
  39. m-0e36dc876e784ecbaa8a9404a6461f1d/tags/mlflow.source.type +1 -0
  40. m-0e36dc876e784ecbaa8a9404a6461f1d/tags/mlflow.user +1 -0
  41. m-1ded0e4d2c644aa88e68e0c422ddc22e/artifacts/MLmodel +19 -0
  42. m-1ded0e4d2c644aa88e68e0c422ddc22e/artifacts/conda.yaml +12 -0
  43. m-1ded0e4d2c644aa88e68e0c422ddc22e/artifacts/python_env.yaml +7 -0
  44. m-1ded0e4d2c644aa88e68e0c422ddc22e/artifacts/python_model.pkl +3 -0
  45. m-1ded0e4d2c644aa88e68e0c422ddc22e/artifacts/requirements.txt +5 -0
  46. m-1ded0e4d2c644aa88e68e0c422ddc22e/meta.yaml +10 -0
  47. m-1ded0e4d2c644aa88e68e0c422ddc22e/metrics/Bogor +1 -0
  48. m-1ded0e4d2c644aa88e68e0c422ddc22e/metrics/Bojong Gede +1 -0
  49. m-1ded0e4d2c644aa88e68e0c422ddc22e/metrics/Cawang +1 -0
  50. m-1ded0e4d2c644aa88e68e0c422ddc22e/metrics/Cikini +1 -0
m-0e36dc876e784ecbaa8a9404a6461f1d/artifacts/MLmodel ADDED
@@ -0,0 +1,19 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ artifact_path: file:///C:/Users/acer/Downloads/JagoanIT/mlruns/0/models/m-0e36dc876e784ecbaa8a9404a6461f1d/artifacts
2
+ flavors:
3
+ python_function:
4
+ cloudpickle_version: 3.1.1
5
+ code: null
6
+ env:
7
+ conda: conda.yaml
8
+ virtualenv: python_env.yaml
9
+ loader_module: mlflow.pyfunc.model
10
+ python_model: python_model.pkl
11
+ python_version: 3.13.1
12
+ streamable: false
13
+ mlflow_version: 3.1.1
14
+ model_id: m-0e36dc876e784ecbaa8a9404a6461f1d
15
+ model_size_bytes: 193
16
+ model_uuid: m-0e36dc876e784ecbaa8a9404a6461f1d
17
+ prompts: null
18
+ run_id: 9a425cd0cecc439e98019f725e163a10
19
+ utc_time_created: '2025-06-25 12:56:52.292572'
m-0e36dc876e784ecbaa8a9404a6461f1d/artifacts/conda.yaml ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ channels:
2
+ - conda-forge
3
+ dependencies:
4
+ - python=3.13.1
5
+ - pip<=24.3.1
6
+ - pip:
7
+ - mlflow==3.1.1
8
+ - cloudpickle==3.1.1
9
+ - numpy==2.3.0
10
+ - pandas==2.3.0
11
+ - scipy==1.15.3
12
+ name: mlflow-env
m-0e36dc876e784ecbaa8a9404a6461f1d/artifacts/python_env.yaml ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ python: 3.13.1
2
+ build_dependencies:
3
+ - pip==24.3.1
4
+ - setuptools
5
+ - wheel
6
+ dependencies:
7
+ - -r requirements.txt
m-0e36dc876e784ecbaa8a9404a6461f1d/artifacts/python_model.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:aa48bb0731a1408e00ba99ec1972848694b8961c1b4745f1864b3125ca2623d4
3
+ size 193
m-0e36dc876e784ecbaa8a9404a6461f1d/artifacts/requirements.txt ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ mlflow==3.1.1
2
+ cloudpickle==3.1.1
3
+ numpy==2.3.0
4
+ pandas==2.3.0
5
+ scipy==1.15.3
m-0e36dc876e784ecbaa8a9404a6461f1d/meta.yaml ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ artifact_location: file:///C:/Users/acer/Downloads/JagoanIT/mlruns/0/models/m-0e36dc876e784ecbaa8a9404a6461f1d/artifacts
2
+ creation_timestamp: 1750856212189
3
+ experiment_id: '0'
4
+ last_updated_timestamp: 1750856215366
5
+ model_id: m-0e36dc876e784ecbaa8a9404a6461f1d
6
+ model_type: null
7
+ name: occupancy_predictor_model 2025-06-16 052000
8
+ source_run_id: 9a425cd0cecc439e98019f725e163a10
9
+ status: 2
10
+ status_message: null
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Bogor ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856211766 20.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Bojong Gede ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856211793 31.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Cawang ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856211980 98.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Cikini ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856212031 97.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Cilebut ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856211780 25.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Citayam ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856211808 36.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Depok ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856211822 42.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Depok Baru ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856211838 48.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Duren Kalibata ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856211962 93.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Gondangdia ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856212047 84.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Jakarta Kota ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856212136 20.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Jayakarta ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856212117 32.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Juanda ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856212065 71.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Lenteng Agung ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856211897 70.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Mangga Besar ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856212100 45.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Manggarai ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856212013 110.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Pasar Minggu ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856211928 81.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Pasar Minggu Baru ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856211945 87.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Pondok Cina ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856211852 53.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Sawah Besar ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856212082 58.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Tanjung Barat ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856211912 76.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Tebet ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856211997 104.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Universitas Indonesia ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856211866 59.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/Universitas Pancasila ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856211881 65.0 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/metrics/confidence ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856212156 0.9 0 9a425cd0cecc439e98019f725e163a10
m-0e36dc876e784ecbaa8a9404a6461f1d/params/route ADDED
@@ -0,0 +1 @@
 
 
1
+ ['Bogor', 'Cilebut', 'Bojong Gede', 'Citayam', 'Depok', 'Depok Baru', 'Pondok Cina', 'Universitas Indonesia', 'Universitas Pancasila', 'Lenteng Agung', 'Tanjung Barat', 'Pasar Minggu', 'Pasar Minggu Baru', 'Duren Kalibata', 'Cawang', 'Tebet', 'Manggarai', 'Cikini', 'Gondangdia', 'Juanda', 'Sawah Besar', 'Mangga Besar', 'Jayakarta', 'Jakarta Kota']
m-0e36dc876e784ecbaa8a9404a6461f1d/params/time ADDED
@@ -0,0 +1 @@
 
 
1
+ 2025-06-16 05:20:00
m-0e36dc876e784ecbaa8a9404a6461f1d/params/train_id ADDED
@@ -0,0 +1 @@
 
 
1
+ 123
m-0e36dc876e784ecbaa8a9404a6461f1d/tags/mlflow.modelVersions ADDED
@@ -0,0 +1 @@
 
 
1
+ [{"name": "OccupancyPredictorModel", "version": 7}]
m-0e36dc876e784ecbaa8a9404a6461f1d/tags/mlflow.note.content ADDED
@@ -0,0 +1 @@
 
 
1
+ Okupansi KRL Bogor - Jakarta Kota di 10 menit sebelum jam sibuk pagi dimulai yg berusaha utk mendekati okupansi sebenarnya
m-0e36dc876e784ecbaa8a9404a6461f1d/tags/mlflow.source.git.commit ADDED
@@ -0,0 +1 @@
 
 
1
+ 6a2c91d0a411952d3aeebaf169fd60363683d44d
m-0e36dc876e784ecbaa8a9404a6461f1d/tags/mlflow.source.name ADDED
@@ -0,0 +1 @@
 
 
1
+ c:/Users/acer/Downloads/JagoanIT/test_occupancy_predictor.py
m-0e36dc876e784ecbaa8a9404a6461f1d/tags/mlflow.source.type ADDED
@@ -0,0 +1 @@
 
 
1
+ LOCAL
m-0e36dc876e784ecbaa8a9404a6461f1d/tags/mlflow.user ADDED
@@ -0,0 +1 @@
 
 
1
+ acer
m-1ded0e4d2c644aa88e68e0c422ddc22e/artifacts/MLmodel ADDED
@@ -0,0 +1,19 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ artifact_path: file:///C:/Users/acer/Downloads/JagoanIT/mlruns/0/models/m-1ded0e4d2c644aa88e68e0c422ddc22e/artifacts
2
+ flavors:
3
+ python_function:
4
+ cloudpickle_version: 3.1.1
5
+ code: null
6
+ env:
7
+ conda: conda.yaml
8
+ virtualenv: python_env.yaml
9
+ loader_module: mlflow.pyfunc.model
10
+ python_model: python_model.pkl
11
+ python_version: 3.13.1
12
+ streamable: false
13
+ mlflow_version: 3.1.1
14
+ model_id: m-1ded0e4d2c644aa88e68e0c422ddc22e
15
+ model_size_bytes: 193
16
+ model_uuid: m-1ded0e4d2c644aa88e68e0c422ddc22e
17
+ prompts: null
18
+ run_id: d50ee97990a04604952e5ae17a9ea3c7
19
+ utc_time_created: '2025-06-25 12:57:51.813268'
m-1ded0e4d2c644aa88e68e0c422ddc22e/artifacts/conda.yaml ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ channels:
2
+ - conda-forge
3
+ dependencies:
4
+ - python=3.13.1
5
+ - pip<=24.3.1
6
+ - pip:
7
+ - mlflow==3.1.1
8
+ - cloudpickle==3.1.1
9
+ - numpy==2.3.0
10
+ - pandas==2.3.0
11
+ - scipy==1.15.3
12
+ name: mlflow-env
m-1ded0e4d2c644aa88e68e0c422ddc22e/artifacts/python_env.yaml ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ python: 3.13.1
2
+ build_dependencies:
3
+ - pip==24.3.1
4
+ - setuptools
5
+ - wheel
6
+ dependencies:
7
+ - -r requirements.txt
m-1ded0e4d2c644aa88e68e0c422ddc22e/artifacts/python_model.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:aa48bb0731a1408e00ba99ec1972848694b8961c1b4745f1864b3125ca2623d4
3
+ size 193
m-1ded0e4d2c644aa88e68e0c422ddc22e/artifacts/requirements.txt ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ mlflow==3.1.1
2
+ cloudpickle==3.1.1
3
+ numpy==2.3.0
4
+ pandas==2.3.0
5
+ scipy==1.15.3
m-1ded0e4d2c644aa88e68e0c422ddc22e/meta.yaml ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ artifact_location: file:///C:/Users/acer/Downloads/JagoanIT/mlruns/0/models/m-1ded0e4d2c644aa88e68e0c422ddc22e/artifacts
2
+ creation_timestamp: 1750856271705
3
+ experiment_id: '0'
4
+ last_updated_timestamp: 1750856275035
5
+ model_id: m-1ded0e4d2c644aa88e68e0c422ddc22e
6
+ model_type: null
7
+ name: occupancy_predictor_model 2025-06-15 100000
8
+ source_run_id: d50ee97990a04604952e5ae17a9ea3c7
9
+ status: 2
10
+ status_message: null
m-1ded0e4d2c644aa88e68e0c422ddc22e/metrics/Bogor ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856271233 20.0 0 d50ee97990a04604952e5ae17a9ea3c7
m-1ded0e4d2c644aa88e68e0c422ddc22e/metrics/Bojong Gede ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856271264 28.0 0 d50ee97990a04604952e5ae17a9ea3c7
m-1ded0e4d2c644aa88e68e0c422ddc22e/metrics/Cawang ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856271474 76.0 0 d50ee97990a04604952e5ae17a9ea3c7
m-1ded0e4d2c644aa88e68e0c422ddc22e/metrics/Cikini ADDED
@@ -0,0 +1 @@
 
 
1
+ 1750856271533 75.0 0 d50ee97990a04604952e5ae17a9ea3c7