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  1. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260318_033129/_arf_generate.py +6 -0
  2. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260318_033129/_arf_train.py +19 -0
  3. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260318_033129/gen_20260318_033228.log +47 -0
  4. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260318_033129/train_20260318_033129.log +4 -0
  5. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/_arf_generate.py +6 -0
  6. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/_arf_train.py +19 -0
  7. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/gen_20260321_064510.log +47 -0
  8. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/gen_20260330_065300.log +47 -0
  9. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/input_snapshot.json +36 -0
  10. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/public_gate/normalized_schema_snapshot.json +467 -0
  11. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/public_gate/public_gate_report.json +37 -0
  12. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/public_gate/staged_input_manifest.json +472 -0
  13. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/runtime_result.json +14 -0
  14. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/staged/arf/adapter_report.json +7 -0
  15. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/staged/arf/adapter_transforms_applied.json +1 -0
  16. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/staged/arf/model_input_manifest.json +474 -0
  17. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/staged/public/staged_features.json +117 -0
  18. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/staged/public/test.csv +0 -0
  19. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/staged/public/train.csv +0 -0
  20. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/staged/public/val.csv +0 -0
  21. SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/train_20260321_064412.log +4 -0
  22. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260318_033041/ctgan_metadata.json +96 -0
  23. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260318_033041/gen_20260318_033605.log +0 -0
  24. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260318_033041/models_300epochs/train_20260318_033041.log +2 -0
  25. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/ctgan_metadata.json +96 -0
  26. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/gen_20260321_070431.log +0 -0
  27. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/gen_20260330_065259.log +0 -0
  28. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/input_snapshot.json +36 -0
  29. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/models_300epochs/train_20260321_065610.log +0 -0
  30. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/public_gate/normalized_schema_snapshot.json +467 -0
  31. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/public_gate/public_gate_report.json +37 -0
  32. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/public_gate/staged_input_manifest.json +472 -0
  33. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/runtime_result.json +14 -0
  34. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/staged/ctgan/adapter_report.json +7 -0
  35. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/staged/ctgan/adapter_transforms_applied.json +1 -0
  36. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/staged/ctgan/model_input_manifest.json +474 -0
  37. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/staged/public/staged_features.json +117 -0
  38. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/staged/public/test.csv +0 -0
  39. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/staged/public/train.csv +0 -0
  40. SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/staged/public/val.csv +0 -0
  41. SynthesizePipeline_Archive/output-SpecializedModels/c5/realtabformer/input_snapshot.json +36 -0
  42. SynthesizePipeline_Archive/output-SpecializedModels/c5/realtabformer/public_gate/normalized_schema_snapshot.json +467 -0
  43. SynthesizePipeline_Archive/output-SpecializedModels/c5/realtabformer/public_gate/public_gate_report.json +37 -0
  44. SynthesizePipeline_Archive/output-SpecializedModels/c5/realtabformer/public_gate/staged_input_manifest.json +472 -0
  45. SynthesizePipeline_Archive/output-SpecializedModels/c5/realtabformer/rtf-c5-20260318_043736/realtabformer_features.json +140 -0
  46. SynthesizePipeline_Archive/output-SpecializedModels/c5/realtabformer/rtf-c5-20260319_065651/gen_20260319_075928.log +13 -0
  47. SynthesizePipeline_Archive/output-SpecializedModels/c5/realtabformer/rtf-c5-20260319_065651/realtabformer_features.json +140 -0
  48. SynthesizePipeline_Archive/output-SpecializedModels/c5/realtabformer/rtf-c5-20260319_065651/train_20260319_065651.log +0 -0
  49. SynthesizePipeline_Archive/output-SpecializedModels/c5/realtabformer/rtf-c5-20260321_191627/gen_20260321_203307.log +13 -0
  50. SynthesizePipeline_Archive/output-SpecializedModels/c5/realtabformer/rtf-c5-20260321_191627/input_snapshot.json +36 -0
SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260318_033129/_arf_generate.py ADDED
@@ -0,0 +1,6 @@
 
 
 
 
 
 
 
1
+ import pickle
2
+ with open("/work/output-SpecializedModels/c5/arf/arf-c5-20260318_033129/arf_model.pkl", "rb") as f:
3
+ model = pickle.load(f)
4
+ syn = model.forge(n=6732)
5
+ syn.to_csv("/work/output-SpecializedModels/c5/arf/arf-c5-20260318_033129/arf-c5-6732-20260318_033228.csv", index=False)
6
+ print(f"[ARF] Generated 6732 rows -> /work/output-SpecializedModels/c5/arf/arf-c5-20260318_033129/arf-c5-6732-20260318_033228.csv")
SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260318_033129/_arf_train.py ADDED
@@ -0,0 +1,19 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import pickle
2
+ import pandas as pd
3
+ from arfpy import arf
4
+
5
+ df = pd.read_csv("/work/DatasetNew/c5/c5-train.csv")
6
+ df = df.dropna(axis=1, how="all")
7
+ print(f"[ARF] Training on {len(df)} rows, {len(df.columns)} cols")
8
+
9
+ model = arf.arf(x=df)
10
+ if hasattr(model, "fit"):
11
+ model.fit()
12
+ elif hasattr(model, "forde"):
13
+ model.forde()
14
+ else:
15
+ raise RuntimeError("arfpy API: no fit() / forde()")
16
+
17
+ with open("/work/output-SpecializedModels/c5/arf/arf-c5-20260318_033129/arf_model.pkl", "wb") as f:
18
+ pickle.dump(model, f)
19
+ print(f"[ARF] Model saved -> /work/output-SpecializedModels/c5/arf/arf-c5-20260318_033129/arf_model.pkl")
SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260318_033129/gen_20260318_033228.log ADDED
@@ -0,0 +1,47 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
2
+ if self.factor_cols[j]:
3
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
4
+ if self.factor_cols[j]:
5
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
6
+ if self.factor_cols[j]:
7
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
8
+ if self.factor_cols[j]:
9
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
10
+ if self.factor_cols[j]:
11
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
12
+ if self.factor_cols[j]:
13
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
14
+ if self.factor_cols[j]:
15
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
16
+ if self.factor_cols[j]:
17
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
18
+ if self.factor_cols[j]:
19
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
20
+ if self.factor_cols[j]:
21
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
22
+ if self.factor_cols[j]:
23
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
24
+ if self.factor_cols[j]:
25
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
26
+ if self.factor_cols[j]:
27
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
28
+ if self.factor_cols[j]:
29
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
30
+ if self.factor_cols[j]:
31
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
32
+ if self.factor_cols[j]:
33
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
34
+ if self.factor_cols[j]:
35
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
36
+ if self.factor_cols[j]:
37
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
38
+ if self.factor_cols[j]:
39
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
40
+ if self.factor_cols[j]:
41
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
42
+ if self.factor_cols[j]:
43
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
44
+ if self.factor_cols[j]:
45
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
46
+ if self.factor_cols[j]:
47
+ [ARF] Generated 6732 rows -> /work/output-SpecializedModels/c5/arf/arf-c5-20260318_033129/arf-c5-6732-20260318_033228.csv
SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260318_033129/train_20260318_033129.log ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ [ARF] Training on 6732 rows, 23 cols
2
+ Initial accuracy is 0.9986631016042781
3
+ Iteration number 1 reached accuracy of 0.4215686274509804.
4
+ [ARF] Model saved -> /work/output-SpecializedModels/c5/arf/arf-c5-20260318_033129/arf_model.pkl
SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/_arf_generate.py ADDED
@@ -0,0 +1,6 @@
 
 
 
 
 
 
 
1
+ import pickle
2
+ with open("/work/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/arf_model.pkl", "rb") as f:
3
+ model = pickle.load(f)
4
+ syn = model.forge(n=6732)
5
+ syn.to_csv("/work/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/arf-c5-6732-20260330_065300.csv", index=False)
6
+ print(f"[ARF] Generated 6732 rows -> /work/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/arf-c5-6732-20260330_065300.csv")
SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/_arf_train.py ADDED
@@ -0,0 +1,19 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import pickle
2
+ import pandas as pd
3
+ from arfpy import arf
4
+
5
+ df = pd.read_csv("/work/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/staged/public/train.csv")
6
+ df = df.dropna(axis=1, how="all")
7
+ print(f"[ARF] Training on {len(df)} rows, {len(df.columns)} cols")
8
+
9
+ model = arf.arf(x=df)
10
+ if hasattr(model, "fit"):
11
+ model.fit()
12
+ elif hasattr(model, "forde"):
13
+ model.forde()
14
+ else:
15
+ raise RuntimeError("arfpy API: no fit() / forde()")
16
+
17
+ with open("/work/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/arf_model.pkl", "wb") as f:
18
+ pickle.dump(model, f)
19
+ print(f"[ARF] Model saved -> /work/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/arf_model.pkl")
SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/gen_20260321_064510.log ADDED
@@ -0,0 +1,47 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
2
+ if self.factor_cols[j]:
3
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
4
+ if self.factor_cols[j]:
5
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
6
+ if self.factor_cols[j]:
7
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
8
+ if self.factor_cols[j]:
9
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
10
+ if self.factor_cols[j]:
11
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
12
+ if self.factor_cols[j]:
13
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
14
+ if self.factor_cols[j]:
15
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
16
+ if self.factor_cols[j]:
17
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
18
+ if self.factor_cols[j]:
19
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
20
+ if self.factor_cols[j]:
21
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
22
+ if self.factor_cols[j]:
23
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
24
+ if self.factor_cols[j]:
25
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
26
+ if self.factor_cols[j]:
27
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
28
+ if self.factor_cols[j]:
29
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
30
+ if self.factor_cols[j]:
31
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
32
+ if self.factor_cols[j]:
33
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
34
+ if self.factor_cols[j]:
35
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
36
+ if self.factor_cols[j]:
37
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
38
+ if self.factor_cols[j]:
39
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
40
+ if self.factor_cols[j]:
41
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
42
+ if self.factor_cols[j]:
43
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
44
+ if self.factor_cols[j]:
45
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
46
+ if self.factor_cols[j]:
47
+ [ARF] Generated 1000 rows -> /work/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/arf-c5-1000-20260321_064510.csv
SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/gen_20260330_065300.log ADDED
@@ -0,0 +1,47 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
2
+ if self.factor_cols[j]:
3
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
4
+ if self.factor_cols[j]:
5
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
6
+ if self.factor_cols[j]:
7
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
8
+ if self.factor_cols[j]:
9
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
10
+ if self.factor_cols[j]:
11
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
12
+ if self.factor_cols[j]:
13
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
14
+ if self.factor_cols[j]:
15
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
16
+ if self.factor_cols[j]:
17
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
18
+ if self.factor_cols[j]:
19
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
20
+ if self.factor_cols[j]:
21
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
22
+ if self.factor_cols[j]:
23
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
24
+ if self.factor_cols[j]:
25
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
26
+ if self.factor_cols[j]:
27
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
28
+ if self.factor_cols[j]:
29
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
30
+ if self.factor_cols[j]:
31
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
32
+ if self.factor_cols[j]:
33
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
34
+ if self.factor_cols[j]:
35
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
36
+ if self.factor_cols[j]:
37
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
38
+ if self.factor_cols[j]:
39
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
40
+ if self.factor_cols[j]:
41
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
42
+ if self.factor_cols[j]:
43
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
44
+ if self.factor_cols[j]:
45
+ /usr/local/lib/python3.10/site-packages/arfpy/arf.py:329: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
46
+ if self.factor_cols[j]:
47
+ [ARF] Generated 6732 rows -> /work/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/arf-c5-6732-20260330_065300.csv
SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/input_snapshot.json ADDED
@@ -0,0 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "dataset_id": "c5",
3
+ "model": "arf",
4
+ "inputs": {
5
+ "train_csv": {
6
+ "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c5/c5-train.csv",
7
+ "exists": true,
8
+ "size": 1004346,
9
+ "sha256": "47ca8fcb0dce8411cee7c20652d6bf10a48a4c284cef58267e775b807c625180"
10
+ },
11
+ "val_csv": {
12
+ "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c5/c5-val.csv",
13
+ "exists": true,
14
+ "size": 125666,
15
+ "sha256": "599dbe0d059984263e88e20a64ae75c0f9795a6ee662c7ae3d13fe4db35753c2"
16
+ },
17
+ "test_csv": {
18
+ "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c5/c5-test.csv",
19
+ "exists": true,
20
+ "size": 126062,
21
+ "sha256": "f4eab85438337cfa2fd60a783388c9bb9f2a67a8c077d09f929fe34ee2895c28"
22
+ },
23
+ "profile_json": {
24
+ "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c5/c5-dataset_profile.json",
25
+ "exists": true,
26
+ "size": 8949,
27
+ "sha256": "74d201cb6f2a25d865c87f0421b9f9c5969d2edfd8fbae898594ff626b33e393"
28
+ },
29
+ "contract_json": {
30
+ "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c5/c5-dataset_contract_v1.json",
31
+ "exists": true,
32
+ "size": 11183,
33
+ "sha256": "df30b6c2fb9044e5c99b3257357a58462928289a836a9cf591e2f754f49bf729"
34
+ }
35
+ }
36
+ }
SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/public_gate/normalized_schema_snapshot.json ADDED
@@ -0,0 +1,467 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "dataset_id": "c5",
3
+ "target_column": "class",
4
+ "task_type": "classification",
5
+ "columns": [
6
+ {
7
+ "name": "class",
8
+ "role": "target",
9
+ "semantic_type": "categorical",
10
+ "nullable": false,
11
+ "missing_tokens": [],
12
+ "parse_format": null,
13
+ "impute_strategy": "mode",
14
+ "profile_stats": {
15
+ "missing_rate": 0.0,
16
+ "unique_count": 2,
17
+ "unique_ratio": 0.000297,
18
+ "example_values": [
19
+ "EDIBLE",
20
+ "POISONOUS"
21
+ ]
22
+ }
23
+ },
24
+ {
25
+ "name": "cap-shape",
26
+ "role": "feature",
27
+ "semantic_type": "categorical",
28
+ "nullable": false,
29
+ "missing_tokens": [],
30
+ "parse_format": null,
31
+ "impute_strategy": "mode",
32
+ "profile_stats": {
33
+ "missing_rate": 0.0,
34
+ "unique_count": 6,
35
+ "unique_ratio": 0.000891,
36
+ "example_values": [
37
+ "CONVEX",
38
+ "BELL",
39
+ "FLAT",
40
+ "KNOBBED",
41
+ "CONICAL"
42
+ ]
43
+ }
44
+ },
45
+ {
46
+ "name": "cap-surface",
47
+ "role": "feature",
48
+ "semantic_type": "categorical",
49
+ "nullable": false,
50
+ "missing_tokens": [],
51
+ "parse_format": null,
52
+ "impute_strategy": "mode",
53
+ "profile_stats": {
54
+ "missing_rate": 0.0,
55
+ "unique_count": 4,
56
+ "unique_ratio": 0.000594,
57
+ "example_values": [
58
+ "SCALY",
59
+ "SMOOTH",
60
+ "FIBROUS",
61
+ "GROOVES"
62
+ ]
63
+ }
64
+ },
65
+ {
66
+ "name": "cap-color",
67
+ "role": "feature",
68
+ "semantic_type": "categorical",
69
+ "nullable": false,
70
+ "missing_tokens": [],
71
+ "parse_format": null,
72
+ "impute_strategy": "mode",
73
+ "profile_stats": {
74
+ "missing_rate": 0.0,
75
+ "unique_count": 10,
76
+ "unique_ratio": 0.001485,
77
+ "example_values": [
78
+ "YELLOW",
79
+ "GRAY",
80
+ "BUFF",
81
+ "WHITE",
82
+ "BROWN"
83
+ ]
84
+ }
85
+ },
86
+ {
87
+ "name": "bruises?",
88
+ "role": "feature",
89
+ "semantic_type": "categorical",
90
+ "nullable": false,
91
+ "missing_tokens": [],
92
+ "parse_format": null,
93
+ "impute_strategy": "mode",
94
+ "profile_stats": {
95
+ "missing_rate": 0.0,
96
+ "unique_count": 2,
97
+ "unique_ratio": 0.000297,
98
+ "example_values": [
99
+ "BRUISES",
100
+ "NO"
101
+ ]
102
+ }
103
+ },
104
+ {
105
+ "name": "odor",
106
+ "role": "feature",
107
+ "semantic_type": "categorical",
108
+ "nullable": true,
109
+ "missing_tokens": [
110
+ "NONE"
111
+ ],
112
+ "parse_format": null,
113
+ "impute_strategy": "mode",
114
+ "profile_stats": {
115
+ "missing_rate": 0.453209,
116
+ "unique_count": 8,
117
+ "unique_ratio": 0.002173,
118
+ "example_values": [
119
+ "ALMOND",
120
+ "FOUL",
121
+ "FISHY",
122
+ "SPICY",
123
+ "ANISE"
124
+ ]
125
+ }
126
+ },
127
+ {
128
+ "name": "gill-attachment",
129
+ "role": "feature",
130
+ "semantic_type": "categorical",
131
+ "nullable": false,
132
+ "missing_tokens": [],
133
+ "parse_format": null,
134
+ "impute_strategy": "mode",
135
+ "profile_stats": {
136
+ "missing_rate": 0.0,
137
+ "unique_count": 2,
138
+ "unique_ratio": 0.000297,
139
+ "example_values": [
140
+ "FREE",
141
+ "ATTACHED"
142
+ ]
143
+ }
144
+ },
145
+ {
146
+ "name": "gill-spacing",
147
+ "role": "feature",
148
+ "semantic_type": "categorical",
149
+ "nullable": false,
150
+ "missing_tokens": [],
151
+ "parse_format": null,
152
+ "impute_strategy": "mode",
153
+ "profile_stats": {
154
+ "missing_rate": 0.0,
155
+ "unique_count": 2,
156
+ "unique_ratio": 0.000297,
157
+ "example_values": [
158
+ "CLOSE",
159
+ "CROWDED"
160
+ ]
161
+ }
162
+ },
163
+ {
164
+ "name": "gill-size",
165
+ "role": "feature",
166
+ "semantic_type": "categorical",
167
+ "nullable": false,
168
+ "missing_tokens": [],
169
+ "parse_format": null,
170
+ "impute_strategy": "mode",
171
+ "profile_stats": {
172
+ "missing_rate": 0.0,
173
+ "unique_count": 2,
174
+ "unique_ratio": 0.000297,
175
+ "example_values": [
176
+ "BROAD",
177
+ "NARROW"
178
+ ]
179
+ }
180
+ },
181
+ {
182
+ "name": "gill-color",
183
+ "role": "feature",
184
+ "semantic_type": "categorical",
185
+ "nullable": false,
186
+ "missing_tokens": [],
187
+ "parse_format": null,
188
+ "impute_strategy": "mode",
189
+ "profile_stats": {
190
+ "missing_rate": 0.0,
191
+ "unique_count": 12,
192
+ "unique_ratio": 0.001783,
193
+ "example_values": [
194
+ "BROWN",
195
+ "BLACK",
196
+ "GRAY",
197
+ "PINK",
198
+ "CHOCOLATE"
199
+ ]
200
+ }
201
+ },
202
+ {
203
+ "name": "stalk-shape",
204
+ "role": "feature",
205
+ "semantic_type": "categorical",
206
+ "nullable": false,
207
+ "missing_tokens": [],
208
+ "parse_format": null,
209
+ "impute_strategy": "mode",
210
+ "profile_stats": {
211
+ "missing_rate": 0.0,
212
+ "unique_count": 2,
213
+ "unique_ratio": 0.000297,
214
+ "example_values": [
215
+ "ENLARGING",
216
+ "TAPERING"
217
+ ]
218
+ }
219
+ },
220
+ {
221
+ "name": "stalk-root",
222
+ "role": "feature",
223
+ "semantic_type": "categorical",
224
+ "nullable": true,
225
+ "missing_tokens": [
226
+ "?"
227
+ ],
228
+ "parse_format": null,
229
+ "impute_strategy": "mode",
230
+ "profile_stats": {
231
+ "missing_rate": 0.295009,
232
+ "unique_count": 4,
233
+ "unique_ratio": 0.000843,
234
+ "example_values": [
235
+ "CLUB",
236
+ "BULBOUS",
237
+ "EQUAL",
238
+ "ROOTED"
239
+ ]
240
+ }
241
+ },
242
+ {
243
+ "name": "stalk-surface-above-ring",
244
+ "role": "feature",
245
+ "semantic_type": "categorical",
246
+ "nullable": false,
247
+ "missing_tokens": [],
248
+ "parse_format": null,
249
+ "impute_strategy": "mode",
250
+ "profile_stats": {
251
+ "missing_rate": 0.0,
252
+ "unique_count": 4,
253
+ "unique_ratio": 0.000594,
254
+ "example_values": [
255
+ "SMOOTH",
256
+ "SILKY",
257
+ "FIBROUS",
258
+ "SCALY"
259
+ ]
260
+ }
261
+ },
262
+ {
263
+ "name": "stalk-surface-below-ring",
264
+ "role": "feature",
265
+ "semantic_type": "categorical",
266
+ "nullable": false,
267
+ "missing_tokens": [],
268
+ "parse_format": null,
269
+ "impute_strategy": "mode",
270
+ "profile_stats": {
271
+ "missing_rate": 0.0,
272
+ "unique_count": 4,
273
+ "unique_ratio": 0.000594,
274
+ "example_values": [
275
+ "SMOOTH",
276
+ "SILKY",
277
+ "FIBROUS",
278
+ "SCALY"
279
+ ]
280
+ }
281
+ },
282
+ {
283
+ "name": "stalk-color-above-ring",
284
+ "role": "feature",
285
+ "semantic_type": "categorical",
286
+ "nullable": false,
287
+ "missing_tokens": [],
288
+ "parse_format": null,
289
+ "impute_strategy": "mode",
290
+ "profile_stats": {
291
+ "missing_rate": 0.0,
292
+ "unique_count": 9,
293
+ "unique_ratio": 0.001337,
294
+ "example_values": [
295
+ "WHITE",
296
+ "BROWN",
297
+ "PINK",
298
+ "BUFF",
299
+ "GRAY"
300
+ ]
301
+ }
302
+ },
303
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+ "feature_name": "stalk-root",
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+ "data_type": "categorical",
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+ },
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+ "feature_name": "stalk-surface-above-ring",
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+ "data_type": "categorical",
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+ "feature_name": "stalk-surface-below-ring",
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+ },
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+ },
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+ "is_target": false
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+ },
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+ {
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+ "feature_name": "spore-print-color",
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+ "data_type": "categorical",
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+ },
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+ {
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+ "feature_name": "population",
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+ },
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SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/staged/public/test.csv ADDED
The diff for this file is too large to render. See raw diff
 
SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/staged/public/train.csv ADDED
The diff for this file is too large to render. See raw diff
 
SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/staged/public/val.csv ADDED
The diff for this file is too large to render. See raw diff
 
SynthesizePipeline_Archive/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/train_20260321_064412.log ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ [ARF] Training on 6732 rows, 23 cols
2
+ Initial accuracy is 0.9982917409387998
3
+ Iteration number 1 reached accuracy of 0.43122400475341655.
4
+ [ARF] Model saved -> /work/output-SpecializedModels/c5/arf/arf-c5-20260321_064412/arf_model.pkl
SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260318_033041/ctgan_metadata.json ADDED
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File without changes
SynthesizePipeline_Archive/output-SpecializedModels/c5/ctgan/ctgan-c5-20260318_033041/models_300epochs/train_20260318_033041.log ADDED
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1
+ /opt/conda/lib/python3.10/site-packages/torch/autograd/graph.py:841: UserWarning: Attempting to run cuBLAS, but there was no current CUDA context! Attempting to set the primary context... (Triggered internally at /pytorch/aten/src/ATen/cuda/CublasHandlePool.cpp:270.)
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+ return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
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