precommit: end-of-file-fixer (microsoft#929)

* precommit: end-of-file-fixer

* exclude .gitignore

* apply

---------

Co-authored-by: Shaokun <[email protected]>

.coveragerc

@@ -2,4 +2,4 @@
 branch = True
 source = flaml
 omit =
-  *test*
+  *test*

.devcontainer/devcontainer.json

@@ -10,4 +10,4 @@
         "terminal.integrated.defaultProfile.linux": "bash"
     },
     "updateContentCommand": "pip install -e .[test,notebook] && pre-commit install"
-}
+}

.flake8

@@ -2,4 +2,4 @@
 ignore = E203, E266, E501, W503, F403, F401, C901
 max-line-length = 127
 max-complexity = 10
-select = B,C,E,F,W,T4,B9
+select = B,C,E,F,W,T4,B9

.github/workflows/python-package.yml

@@ -122,4 +122,4 @@ jobs:
   #         GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
   #         BRANCH: gh-pages
   #         FOLDER: docs/_build/html
-  #         CLEAN: true
+  #         CLEAN: true

.gitignore

@@ -159,4 +159,3 @@ automl.pkl
 
 test/nlp/testtmp.py
 test/nlp/testtmpfl.py
-

.pre-commit-config.yaml

@@ -24,7 +24,9 @@ repos:
     - id: check-toml
     - id: check-json
     - id: check-byte-order-marker
+      exclude: .gitignore
     - id: check-merge-conflict
     - id: detect-private-key
     - id: trailing-whitespace
-    - id: no-commit-to-branch
+    - id: end-of-file-fixer
+    - id: no-commit-to-branch

SECURITY.md

@@ -38,4 +38,4 @@ We prefer all communications to be in English.
 
 Microsoft follows the principle of [Coordinated Vulnerability Disclosure](https://www.microsoft.com/en-us/msrc/cvd).
 
-<!-- END MICROSOFT SECURITY.MD BLOCK -->
+<!-- END MICROSOFT SECURITY.MD BLOCK -->

flaml/automl/automl.py

@@ -346,7 +346,10 @@ def _prepare_sample_train_data(self, sample_size: int):
 
     @staticmethod
     def _compute_with_config_base(
-        config_w_resource: dict, state: AutoMLState, estimator: str, is_report: bool = True
+        config_w_resource: dict,
+        state: AutoMLState,
+        estimator: str,
+        is_report: bool = True,
     ) -> dict:
         if "FLAML_sample_size" in config_w_resource:
             sample_size = int(config_w_resource["FLAML_sample_size"])

flaml/automl/nlp/README.md

@@ -23,5 +23,3 @@ Our findings on troubleshooting fine-tuning the Electra and RoBERTa model for th
     booktitle={ACL-IJCNLP},
 }
 ```
-
-

flaml/default/README.md

@@ -181,4 +181,4 @@ For more technical details, please check our research paper.
     year={2022},
     journal={arXiv preprint arXiv:2202.09927},
 }
-```
+```

flaml/default/all/binary.json

@@ -943,4 +943,4 @@
         "extra_tree/bank-marketing",
         "extra_tree/default"
     ]
-}
+}

flaml/default/all/multiclass.json

@@ -1325,4 +1325,4 @@
         "extra_tree/fried",
         "extra_tree/default"
     ]
-}
+}

flaml/default/all/regression.json

@@ -882,4 +882,4 @@
         "extra_tree/dilbert",
         "extra_tree/particulate-matter"
     ]
-}
+}

flaml/default/extra_tree/binary.json

@@ -358,4 +358,4 @@
         "bank-marketing",
         "default"
     ]
-}
+}

flaml/default/extra_tree/multiclass.json

@@ -307,4 +307,4 @@
         "fried",
         "default"
     ]
-}
+}

flaml/default/extra_tree/regression.json

@@ -309,4 +309,4 @@
         "dilbert",
         "particulate-matter"
     ]
-}
+}

flaml/default/lgbm/binary.json

@@ -367,4 +367,4 @@
         "Dionis",
         "default"
     ]
-}
+}

flaml/default/lgbm/multiclass.json

@@ -413,4 +413,4 @@
         "APSFailure",
         "default"
     ]
-}
+}

flaml/default/lgbm/regression.json

@@ -278,4 +278,4 @@
         "poker",
         "default"
     ]
-}
+}

flaml/default/rf/binary.json

@@ -330,4 +330,4 @@
         "Helena",
         "default"
     ]
-}
+}

flaml/default/rf/multiclass.json

@@ -325,4 +325,4 @@
         "MiniBooNE",
         "default"
     ]
-}
+}

flaml/default/rf/regression.json

@@ -290,4 +290,4 @@
         "bank-marketing",
         "default"
     ]
-}
+}

flaml/default/xgb_limitdepth/binary.json

@@ -326,4 +326,4 @@
         "Amazon_employee_access",
         "default"
     ]
-}
+}

flaml/default/xgb_limitdepth/multiclass.json

@@ -354,4 +354,4 @@
         "vehicle",
         "mfeat-factors"
     ]
-}
+}

flaml/default/xgb_limitdepth/regression.json

@@ -347,4 +347,4 @@
         "bng_echomonths",
         "default"
     ]
-}
+}

flaml/default/xgboost/binary.json

@@ -372,4 +372,4 @@
         "pol",
         "Amazon_employee_access"
     ]
-}
+}

flaml/default/xgboost/multiclass.json

@@ -509,4 +509,4 @@
         "dilbert",
         "jungle_chess_2pcs_raw_endgame_complete"
     ]
-}
+}

flaml/default/xgboost/regression.json

@@ -308,4 +308,4 @@
         "bng_echomonths",
         "house_16H"
     ]
-}
+}

flaml/onlineml/README.md

@@ -44,4 +44,4 @@ autovw = AutoVW(max_live_model_num=5, search_space=search_space_nilr, init_confi
 A user can use the resulting AutoVW instances `autovw` in a similar way to a vanilla Vowpal Wabbit instance, i.e., `pyvw.vw`, to perform online learning by iteratively calling its `predict(data_example)` and `learn(data_example)` functions at each data example.
 
 For more examples, please check out
-[AutoVW notebook](https://github.com/microsoft/FLAML/blob/main/notebook/autovw.ipynb).
+[AutoVW notebook](https://github.com/microsoft/FLAML/blob/main/notebook/autovw.ipynb).

pytest.ini

@@ -2,4 +2,3 @@
 addopts = -m "not conda"
 markers =
     conda: test related to conda forge distribution
-

test/default/extra_tree/2dplanes.json

@@ -1 +1 @@
-{"class": "extra_tree", "hyperparameters": {"n_estimators": 16, "max_features": 1.0, "max_leaves": 54}}
+{"class": "extra_tree", "hyperparameters": {"n_estimators": 16, "max_features": 1.0, "max_leaves": 54}}

test/default/extra_tree/Airlines.json

@@ -1 +1 @@
-{"class": "extra_tree", "hyperparameters": {"n_estimators": 2047, "max_features": 1.0, "max_leaves": 8194, "criterion": "gini", "FLAML_sample_size": 436899}}
+{"class": "extra_tree", "hyperparameters": {"n_estimators": 2047, "max_features": 1.0, "max_leaves": 8194, "criterion": "gini", "FLAML_sample_size": 436899}}

test/default/extra_tree/Albert.json

@@ -1 +1 @@
-{"class": "extra_tree", "hyperparameters": {"n_estimators": 1733, "max_features": 0.3841826938360253, "max_leaves": 32767, "criterion": "entropy", "FLAML_sample_size": 344444}}
+{"class": "extra_tree", "hyperparameters": {"n_estimators": 1733, "max_features": 0.3841826938360253, "max_leaves": 32767, "criterion": "entropy", "FLAML_sample_size": 344444}}

test/default/extra_tree/Amazon_employee_access.json

@@ -1 +1 @@
-{"class": "extra_tree", "hyperparameters": {"n_estimators": 812, "max_features": 1.0, "max_leaves": 1474, "criterion": "entropy"}}
+{"class": "extra_tree", "hyperparameters": {"n_estimators": 812, "max_features": 1.0, "max_leaves": 1474, "criterion": "entropy"}}

test/default/extra_tree/adult.json

@@ -1 +1 @@
-{"class": "extra_tree", "hyperparameters": {"n_estimators": 859, "max_features": 1.0, "max_leaves": 967, "criterion": "entropy"}}
+{"class": "extra_tree", "hyperparameters": {"n_estimators": 859, "max_features": 1.0, "max_leaves": 967, "criterion": "entropy"}}

test/default/extra_tree/bng_breastTumor.json

@@ -1 +1 @@
-{"class": "extra_tree", "hyperparameters": {"n_estimators": 90, "max_features": 1.0, "max_leaves": 1301, "FLAML_sample_size": 94478}}
+{"class": "extra_tree", "hyperparameters": {"n_estimators": 90, "max_features": 1.0, "max_leaves": 1301, "FLAML_sample_size": 94478}}

test/default/extra_tree/bng_pbc.json

@@ -1 +1 @@
-{"class": "extra_tree", "hyperparameters": {"n_estimators": 1211, "max_features": 1.0, "max_leaves": 32767, "FLAML_sample_size": 810000}}
+{"class": "extra_tree", "hyperparameters": {"n_estimators": 1211, "max_features": 1.0, "max_leaves": 32767, "FLAML_sample_size": 810000}}

test/default/extra_tree/car.json

@@ -1 +1 @@
-{"class": "extra_tree", "hyperparameters": {"n_estimators": 333, "max_features": 1.0, "max_leaves": 201, "criterion": "gini"}}
+{"class": "extra_tree", "hyperparameters": {"n_estimators": 333, "max_features": 1.0, "max_leaves": 201, "criterion": "gini"}}

test/default/extra_tree/connect-4.json

@@ -1 +1 @@
-{"class": "extra_tree", "hyperparameters": {"n_estimators": 229, "max_features": 0.5372053700721111, "max_leaves": 11150, "criterion": "entropy"}}
+{"class": "extra_tree", "hyperparameters": {"n_estimators": 229, "max_features": 0.5372053700721111, "max_leaves": 11150, "criterion": "entropy"}}

test/default/extra_tree/default.json

@@ -1 +1 @@
-{"class": "extra_tree", "hyperparameters": {}}
+{"class": "extra_tree", "hyperparameters": {}}

test/default/extra_tree/dilbert.json

@@ -1 +1 @@
-{"class": "extra_tree", "hyperparameters": {"n_estimators": 346, "max_features": 1.0, "max_leaves": 1007, "criterion": "entropy"}}
+{"class": "extra_tree", "hyperparameters": {"n_estimators": 346, "max_features": 1.0, "max_leaves": 1007, "criterion": "entropy"}}

test/default/extra_tree/poker.json

@@ -1 +1 @@
-{"class": "extra_tree", "hyperparameters": {"n_estimators": 1416, "max_features": 1.0, "max_leaves": 32767, "FLAML_sample_size": 830258}}
+{"class": "extra_tree", "hyperparameters": {"n_estimators": 1416, "max_features": 1.0, "max_leaves": 32767, "FLAML_sample_size": 830258}}

test/default/lgbm/2dplanes.json

@@ -1 +1 @@
-{"class": "lgbm", "hyperparameters": {"n_estimators": 103, "num_leaves": 33, "min_child_samples": 4, "learning_rate": 0.05800185361316003, "log_max_bin": 6, "colsample_bytree": 1.0, "reg_alpha": 1.5987124004961213, "reg_lambda": 10.56445079499673}}
+{"class": "lgbm", "hyperparameters": {"n_estimators": 103, "num_leaves": 33, "min_child_samples": 4, "learning_rate": 0.05800185361316003, "log_max_bin": 6, "colsample_bytree": 1.0, "reg_alpha": 1.5987124004961213, "reg_lambda": 10.56445079499673}}

test/default/lgbm/APSFailure.json

@@ -1 +1 @@
-{"class": "lgbm", "hyperparameters": {"n_estimators": 733, "num_leaves": 11, "min_child_samples": 94, "learning_rate": 0.06276798296942972, "log_max_bin": 6, "colsample_bytree": 0.6341928918435795, "reg_alpha": 0.5811038918218691, "reg_lambda": 43.304997517523944}}
+{"class": "lgbm", "hyperparameters": {"n_estimators": 733, "num_leaves": 11, "min_child_samples": 94, "learning_rate": 0.06276798296942972, "log_max_bin": 6, "colsample_bytree": 0.6341928918435795, "reg_alpha": 0.5811038918218691, "reg_lambda": 43.304997517523944}}

test/default/lgbm/Airlines.json

@@ -1 +1 @@
-{"class": "lgbm", "hyperparameters": {"n_estimators": 2541, "num_leaves": 1667, "min_child_samples": 29, "learning_rate": 0.0016660662914022302, "log_max_bin": 8, "colsample_bytree": 0.5157078343718623, "reg_alpha": 0.045792841240713165, "reg_lambda": 0.0012362651138125363, "FLAML_sample_size": 436899}}
+{"class": "lgbm", "hyperparameters": {"n_estimators": 2541, "num_leaves": 1667, "min_child_samples": 29, "learning_rate": 0.0016660662914022302, "log_max_bin": 8, "colsample_bytree": 0.5157078343718623, "reg_alpha": 0.045792841240713165, "reg_lambda": 0.0012362651138125363, "FLAML_sample_size": 436899}}

test/default/lgbm/Albert.json

@@ -1 +1 @@
-{"class": "lgbm", "hyperparameters": {"n_estimators": 12659, "num_leaves": 566, "min_child_samples": 51, "learning_rate": 0.0017248557932071625, "log_max_bin": 10, "colsample_bytree": 0.35373661752616337, "reg_alpha": 0.004824272162679245, "reg_lambda": 8.51563063056529, "FLAML_sample_size": 344444}}
+{"class": "lgbm", "hyperparameters": {"n_estimators": 12659, "num_leaves": 566, "min_child_samples": 51, "learning_rate": 0.0017248557932071625, "log_max_bin": 10, "colsample_bytree": 0.35373661752616337, "reg_alpha": 0.004824272162679245, "reg_lambda": 8.51563063056529, "FLAML_sample_size": 344444}}

test/default/lgbm/Amazon_employee_access.json

@@ -1 +1 @@
-{"class": "lgbm", "hyperparameters": {"n_estimators": 198, "num_leaves": 6241, "min_child_samples": 3, "learning_rate": 0.003807690748728824, "log_max_bin": 10, "colsample_bytree": 0.3192882305722113, "reg_alpha": 0.024630507311503163, "reg_lambda": 0.06738306675149014}}
+{"class": "lgbm", "hyperparameters": {"n_estimators": 198, "num_leaves": 6241, "min_child_samples": 3, "learning_rate": 0.003807690748728824, "log_max_bin": 10, "colsample_bytree": 0.3192882305722113, "reg_alpha": 0.024630507311503163, "reg_lambda": 0.06738306675149014}}

test/default/lgbm/Dionis.json

@@ -1 +1 @@
-{"class": "lgbm", "hyperparameters": {"n_estimators": 362, "num_leaves": 1208, "min_child_samples": 8, "learning_rate": 0.02070742242160566, "log_max_bin": 4, "colsample_bytree": 0.37915528071680865, "reg_alpha": 0.002982599447751338, "reg_lambda": 1.136605174453919, "FLAML_sample_size": 337147}}
+{"class": "lgbm", "hyperparameters": {"n_estimators": 362, "num_leaves": 1208, "min_child_samples": 8, "learning_rate": 0.02070742242160566, "log_max_bin": 4, "colsample_bytree": 0.37915528071680865, "reg_alpha": 0.002982599447751338, "reg_lambda": 1.136605174453919, "FLAML_sample_size": 337147}}

test/default/lgbm/adult.json

@@ -1 +1 @@
-{"class": "lgbm", "hyperparameters": {"n_estimators": 11842, "num_leaves": 31, "min_child_samples": 3, "learning_rate": 0.0015861878568503534, "log_max_bin": 8, "colsample_bytree": 0.3814347840573729, "reg_alpha": 0.0009765625, "reg_lambda": 0.011319689446351965}}
+{"class": "lgbm", "hyperparameters": {"n_estimators": 11842, "num_leaves": 31, "min_child_samples": 3, "learning_rate": 0.0015861878568503534, "log_max_bin": 8, "colsample_bytree": 0.3814347840573729, "reg_alpha": 0.0009765625, "reg_lambda": 0.011319689446351965}}

test/default/lgbm/bng_breastTumor.json

@@ -1 +1 @@
-{"class": "lgbm", "hyperparameters": {"n_estimators": 644, "num_leaves": 40, "min_child_samples": 38, "learning_rate": 0.06007328261566753, "log_max_bin": 5, "colsample_bytree": 0.6950692048656423, "reg_alpha": 0.0009765625, "reg_lambda": 9.849318389111616, "FLAML_sample_size": 94478}}
+{"class": "lgbm", "hyperparameters": {"n_estimators": 644, "num_leaves": 40, "min_child_samples": 38, "learning_rate": 0.06007328261566753, "log_max_bin": 5, "colsample_bytree": 0.6950692048656423, "reg_alpha": 0.0009765625, "reg_lambda": 9.849318389111616, "FLAML_sample_size": 94478}}

test/default/lgbm/bng_pbc.json

@@ -1 +1 @@
-{"class": "lgbm", "hyperparameters": {"n_estimators": 27202, "num_leaves": 848, "min_child_samples": 2, "learning_rate": 0.0019296395751528979, "log_max_bin": 5, "colsample_bytree": 0.7328229531785452, "reg_alpha": 6.112225454676263, "reg_lambda": 0.08606162543586986, "FLAML_sample_size": 810000}}
+{"class": "lgbm", "hyperparameters": {"n_estimators": 27202, "num_leaves": 848, "min_child_samples": 2, "learning_rate": 0.0019296395751528979, "log_max_bin": 5, "colsample_bytree": 0.7328229531785452, "reg_alpha": 6.112225454676263, "reg_lambda": 0.08606162543586986, "FLAML_sample_size": 810000}}

test/default/lgbm/car.json

@@ -1 +1 @@
-{"class": "lgbm", "hyperparameters": {"n_estimators": 311, "num_leaves": 4, "min_child_samples": 5, "learning_rate": 0.5547292134798673, "log_max_bin": 3, "colsample_bytree": 0.9917614238487915, "reg_alpha": 0.0009765625, "reg_lambda": 0.0019177370889840813}}
+{"class": "lgbm", "hyperparameters": {"n_estimators": 311, "num_leaves": 4, "min_child_samples": 5, "learning_rate": 0.5547292134798673, "log_max_bin": 3, "colsample_bytree": 0.9917614238487915, "reg_alpha": 0.0009765625, "reg_lambda": 0.0019177370889840813}}

test/default/lgbm/connect-4.json

@@ -1 +1 @@
-{"class": "lgbm", "hyperparameters": {"n_estimators": 3726, "num_leaves": 155, "min_child_samples": 4, "learning_rate": 0.040941607728296484, "log_max_bin": 5, "colsample_bytree": 0.5326256194627191, "reg_alpha": 0.7408711930398492, "reg_lambda": 0.5467731065349226}}
+{"class": "lgbm", "hyperparameters": {"n_estimators": 3726, "num_leaves": 155, "min_child_samples": 4, "learning_rate": 0.040941607728296484, "log_max_bin": 5, "colsample_bytree": 0.5326256194627191, "reg_alpha": 0.7408711930398492, "reg_lambda": 0.5467731065349226}}

test/default/lgbm/default.json

@@ -1 +1 @@
-{"class": "lgbm", "hyperparameters": {}}
+{"class": "lgbm", "hyperparameters": {}}

test/default/lgbm/dilbert.json

@@ -1 +1 @@
-{"class": "lgbm", "hyperparameters": {"n_estimators": 7325, "num_leaves": 15, "min_child_samples": 6, "learning_rate": 0.009932524214971736, "log_max_bin": 6, "colsample_bytree": 0.8592091503131608, "reg_alpha": 0.0009997224940106115, "reg_lambda": 0.04069855891326503}}
+{"class": "lgbm", "hyperparameters": {"n_estimators": 7325, "num_leaves": 15, "min_child_samples": 6, "learning_rate": 0.009932524214971736, "log_max_bin": 6, "colsample_bytree": 0.8592091503131608, "reg_alpha": 0.0009997224940106115, "reg_lambda": 0.04069855891326503}}

test/default/lgbm/poker.json

@@ -1 +1 @@
-{"class": "lgbm", "hyperparameters": {"n_estimators": 32767, "num_leaves": 372, "min_child_samples": 4, "learning_rate": 0.03517259015200922, "log_max_bin": 5, "colsample_bytree": 1.0, "reg_alpha": 0.02271142170225636, "reg_lambda": 0.001963791798843179, "FLAML_sample_size": 830258}}
+{"class": "lgbm", "hyperparameters": {"n_estimators": 32767, "num_leaves": 372, "min_child_samples": 4, "learning_rate": 0.03517259015200922, "log_max_bin": 5, "colsample_bytree": 1.0, "reg_alpha": 0.02271142170225636, "reg_lambda": 0.001963791798843179, "FLAML_sample_size": 830258}}

test/default/rf/2dplanes.json

@@ -1 +1 @@
-{"class": "rf", "hyperparameters": {"n_estimators": 38, "max_features": 1.0, "max_leaves": 58}}
+{"class": "rf", "hyperparameters": {"n_estimators": 38, "max_features": 1.0, "max_leaves": 58}}

test/default/rf/Airlines.json

@@ -1 +1 @@
-{"class": "rf", "hyperparameters": {"n_estimators": 418, "max_features": 0.5303485415288045, "max_leaves": 6452, "criterion": "entropy", "FLAML_sample_size": 436899}}
+{"class": "rf", "hyperparameters": {"n_estimators": 418, "max_features": 0.5303485415288045, "max_leaves": 6452, "criterion": "entropy", "FLAML_sample_size": 436899}}

test/default/rf/Albert.json

@@ -1 +1 @@
-{"class": "rf", "hyperparameters": {"n_estimators": 2047, "max_features": 0.10091610074262287, "max_leaves": 32767, "criterion": "entropy", "FLAML_sample_size": 344444}}
+{"class": "rf", "hyperparameters": {"n_estimators": 2047, "max_features": 0.10091610074262287, "max_leaves": 32767, "criterion": "entropy", "FLAML_sample_size": 344444}}

test/default/rf/Amazon_employee_access.json

@@ -1 +1 @@
-{"class": "rf", "hyperparameters": {"n_estimators": 501, "max_features": 0.24484242524861066, "max_leaves": 1156, "criterion": "entropy"}}
+{"class": "rf", "hyperparameters": {"n_estimators": 501, "max_features": 0.24484242524861066, "max_leaves": 1156, "criterion": "entropy"}}

test/default/rf/Dionis.json

@@ -1 +1 @@
-{"class": "rf", "hyperparameters": {"n_estimators": 510, "max_features": 0.12094682590862652, "max_leaves": 32767, "criterion": "entropy", "FLAML_sample_size": 337147}}
+{"class": "rf", "hyperparameters": {"n_estimators": 510, "max_features": 0.12094682590862652, "max_leaves": 32767, "criterion": "entropy", "FLAML_sample_size": 337147}}

test/default/rf/adult.json

@@ -1 +1 @@
-{"class": "rf", "hyperparameters": {"n_estimators": 1212, "max_features": 0.3129111648657632, "max_leaves": 779, "criterion": "entropy"}}
+{"class": "rf", "hyperparameters": {"n_estimators": 1212, "max_features": 0.3129111648657632, "max_leaves": 779, "criterion": "entropy"}}

test/default/rf/bng_breastTumor.json

@@ -1 +1 @@
-{"class": "rf", "hyperparameters": {"n_estimators": 288, "max_features": 0.6436380990499977, "max_leaves": 1823, "FLAML_sample_size": 94478}}
+{"class": "rf", "hyperparameters": {"n_estimators": 288, "max_features": 0.6436380990499977, "max_leaves": 1823, "FLAML_sample_size": 94478}}

test/default/rf/bng_pbc.json

@@ -1 +1 @@
-{"class": "rf", "hyperparameters": {"n_estimators": 2047, "max_features": 0.3158919059422144, "max_leaves": 32767, "FLAML_sample_size": 810000}}
+{"class": "rf", "hyperparameters": {"n_estimators": 2047, "max_features": 0.3158919059422144, "max_leaves": 32767, "FLAML_sample_size": 810000}}

test/default/rf/car.json

@@ -1 +1 @@
-{"class": "rf", "hyperparameters": {"n_estimators": 792, "max_features": 1.0, "max_leaves": 67, "criterion": "entropy"}}
+{"class": "rf", "hyperparameters": {"n_estimators": 792, "max_features": 1.0, "max_leaves": 67, "criterion": "entropy"}}

test/default/rf/connect-4.json

@@ -1 +1 @@
-{"class": "rf", "hyperparameters": {"n_estimators": 1907, "max_features": 0.3728618389498168, "max_leaves": 11731, "criterion": "entropy"}}
+{"class": "rf", "hyperparameters": {"n_estimators": 1907, "max_features": 0.3728618389498168, "max_leaves": 11731, "criterion": "entropy"}}

test/default/rf/default.json

@@ -1 +1 @@
-{"class": "rf", "hyperparameters": {}}
+{"class": "rf", "hyperparameters": {}}

test/default/rf/dilbert.json

@@ -1 +1 @@
-{"class": "rf", "hyperparameters": {"n_estimators": 350, "max_features": 0.748250835121453, "max_leaves": 433, "criterion": "entropy"}}
+{"class": "rf", "hyperparameters": {"n_estimators": 350, "max_features": 0.748250835121453, "max_leaves": 433, "criterion": "entropy"}}