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Merge pull request #28 from Bronzila/issue/train_data
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Closes #23 and fixes spelling mistake in interfacing_DEHB example
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@Neeratyoy
Neeratyoy committed Jun 29, 2023
2 parents 26250d3 + b7f7c73 commit 96fa1fc
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Showing 2 changed files with 72 additions and 65 deletions.
2 changes: 1 addition & 1 deletion examples/00_interfacing_DEHB.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -322,7 +322,7 @@
}
],
"source": [
"# allows optimization to restart from the beginning by forgetting al observations\n",
"# allows optimization to restart from the beginning by forgetting all observations\n",
"dehb.reset() \n",
"\n",
"_, _, _ = dehb.run(fevals=20, verbose=False, save_intermediate=True)\n",
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135 changes: 71 additions & 64 deletions examples/01_Optimizing_RandomForest_using_DEHB.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -203,19 +203,20 @@
" dataset = np.random.choice(list(regression.keys()))\n",
" _data = regression[dataset]()\n",
"\n",
" train_X, test_X, train_y, test_y = train_test_split(\n",
" _data.get(\"data\"), \n",
" _data.get(\"target\"), \n",
" test_size=0.1, \n",
" shuffle=True, \n",
" random_state=seed\n",
" train_X, rest_X, train_y, rest_y = train_test_split(\n",
" _data.get(\"data\"), \n",
" _data.get(\"target\"), \n",
" train_size=0.7, \n",
" shuffle=True, \n",
" random_state=seed\n",
" )\n",
" train_X, valid_X, train_y, valid_y = train_test_split(\n",
" _data.get(\"data\"), \n",
" _data.get(\"target\"), \n",
" test_size=0.3, \n",
" shuffle=True, \n",
" random_state=seed\n",
" \n",
" # 10% test and 20% validation data\n",
" valid_X, test_X, valid_y, test_y = train_test_split(\n",
" rest_X, rest_y,\n",
" test_size=0.3333, \n",
" shuffle=True, \n",
" random_state=seed\n",
" )\n",
" return train_X, train_y, valid_X, valid_y, test_X, test_y, dataset"
]
Expand All @@ -231,7 +232,7 @@
"text": [
"wine\n",
"Train size: (124, 13)\n",
"Valid size: (54, 13)\n",
"Valid size: (36, 13)\n",
"Test size: (18, 13)\n"
]
}
Expand Down Expand Up @@ -375,16 +376,17 @@
"name": "stdout",
"output_type": "stream",
"text": [
"254 254 254\n",
"473 473 473\n",
"\n",
"Last evaluated configuration, \n",
"Configuration:\n",
" max_depth, Value: 4\n",
" max_features, Value: 0.7421389151242858\n",
" min_samples_leaf, Value: 3\n",
" min_samples_split, Value: 6\n",
"got a score of -1.0, was evaluated at a budget of 16.67 and took 0.021 seconds to run.\n",
"The additional info attached: {'test_score': 1.0, 'budget': 16.666666666666664}\n"
"Configuration(values={\n",
" 'max_depth': 7,\n",
" 'max_features': 0.669059250229961,\n",
" 'min_samples_leaf': 2,\n",
" 'min_samples_split': 3,\n",
"})\n",
"got a score of -1.0, was evaluated at a budget of 50.00 and took 0.048 seconds to run.\n",
"The additional info attached: {'test_score': 1.0, 'budget': 50.0}\n"
]
}
],
Expand Down Expand Up @@ -418,31 +420,31 @@
"name": "stdout",
"output_type": "stream",
"text": [
"2021-08-11 04:02:25.962 | INFO | dehb.optimizers.dehb:reset:107 - \n",
"\n",
"RESET at 08/11/21 04:02:25 CEST\n",
"\n",
"\u001b[32m2023-06-22 12:00:41.016\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mdehb.optimizers.dehb\u001b[0m:\u001b[36mreset\u001b[0m:\u001b[36m107\u001b[0m - \u001b[1m\n",
"\n",
"2021-08-11 04:02:36.081 | INFO | dehb.optimizers.dehb:reset:107 - \n",
"RESET at 06/22/23 12:00:40 CEST\n",
"\n",
"RESET at 08/11/21 04:02:36 CEST\n",
"\u001b[0m\n",
"\u001b[32m2023-06-22 12:00:51.085\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mdehb.optimizers.dehb\u001b[0m:\u001b[36mreset\u001b[0m:\u001b[36m107\u001b[0m - \u001b[1m\n",
"\n",
"RESET at 06/22/23 12:00:51 CEST\n",
"\n",
"2021-08-11 04:02:46.256 | INFO | dehb.optimizers.dehb:reset:107 - \n",
"\u001b[0m\n",
"\u001b[32m2023-06-22 12:01:01.182\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mdehb.optimizers.dehb\u001b[0m:\u001b[36mreset\u001b[0m:\u001b[36m107\u001b[0m - \u001b[1m\n",
"\n",
"RESET at 08/11/21 04:02:46 CEST\n",
"RESET at 06/22/23 12:01:01 CEST\n",
"\n",
"\u001b[0m\n",
"\u001b[32m2023-06-22 12:01:11.238\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mdehb.optimizers.dehb\u001b[0m:\u001b[36mreset\u001b[0m:\u001b[36m107\u001b[0m - \u001b[1m\n",
"\n",
"2021-08-11 04:02:56.351 | INFO | dehb.optimizers.dehb:reset:107 - \n",
"RESET at 06/22/23 12:01:11 CEST\n",
"\n",
"RESET at 08/11/21 04:02:56 CEST\n",
"\u001b[0m\n",
"\u001b[32m2023-06-22 12:01:21.293\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mdehb.optimizers.dehb\u001b[0m:\u001b[36mreset\u001b[0m:\u001b[36m107\u001b[0m - \u001b[1m\n",
"\n",
"RESET at 06/22/23 12:01:21 CEST\n",
"\n",
"2021-08-11 04:03:06.441 | INFO | dehb.optimizers.dehb:reset:107 - \n",
"\n",
"RESET at 08/11/21 04:03:06 CEST\n",
"\n",
"\n"
"\u001b[0m\n"
]
}
],
Expand Down Expand Up @@ -513,39 +515,44 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Configuration:\n",
" max_depth, Value: 12\n",
" max_features, Value: 0.6810033803746296\n",
" min_samples_leaf, Value: 1\n",
" min_samples_split, Value: 2\n",
"Configuration(values={\n",
" 'max_depth': 13,\n",
" 'max_features': 0.5412753369058052,\n",
" 'min_samples_leaf': 12,\n",
" 'min_samples_split': 14,\n",
"})\n",
" got an accuracy of 1.0 on the test set.\n",
"\n",
"Configuration:\n",
" max_depth, Value: 12\n",
" max_features, Value: 0.7019468557915487\n",
" min_samples_leaf, Value: 1\n",
" min_samples_split, Value: 2\n",
"Configuration(values={\n",
" 'max_depth': 6,\n",
" 'max_features': 0.6764411582074702,\n",
" 'min_samples_leaf': 1,\n",
" 'min_samples_split': 27,\n",
"})\n",
" got an accuracy of 1.0 on the test set.\n",
"\n",
"Configuration:\n",
" max_depth, Value: 14\n",
" max_features, Value: 0.557961004785893\n",
" min_samples_leaf, Value: 4\n",
" min_samples_split, Value: 21\n",
"Configuration(values={\n",
" 'max_depth': 5,\n",
" 'max_features': 0.5862915814751853,\n",
" 'min_samples_leaf': 2,\n",
" 'min_samples_split': 22,\n",
"})\n",
" got an accuracy of 1.0 on the test set.\n",
"\n",
"Configuration:\n",
" max_depth, Value: 10\n",
" max_features, Value: 0.7574798490327812\n",
" min_samples_leaf, Value: 12\n",
" min_samples_split, Value: 3\n",
"Configuration(values={\n",
" 'max_depth': 14,\n",
" 'max_features': 0.5346143393392929,\n",
" 'min_samples_leaf': 5,\n",
" 'min_samples_split': 9,\n",
"})\n",
" got an accuracy of 1.0 on the test set.\n",
"\n",
"Configuration:\n",
" max_depth, Value: 10\n",
" max_features, Value: 0.6303283393470247\n",
" min_samples_leaf, Value: 5\n",
" min_samples_split, Value: 25\n",
"Configuration(values={\n",
" 'max_depth': 4,\n",
" 'max_features': 0.5541455312635835,\n",
" 'min_samples_leaf': 4,\n",
" 'min_samples_split': 10,\n",
"})\n",
" got an accuracy of 1.0 on the test set.\n",
"\n"
]
Expand All @@ -560,9 +567,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "dask",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "dask"
"name": "python3"
},
"language_info": {
"codemirror_mode": {
Expand All @@ -574,7 +581,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.9"
"version": "3.9.16"
}
},
"nbformat": 4,
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