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Merge pull request #15 from LinglongQian/main
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release experiment logs
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@WenjieDu
WenjieDu committed Jun 17, 2024
2 parents b30caad + a9b3b07 commit aea6a78
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24 changes: 21 additions & 3 deletions benchmark_code/read_results.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -2,9 +2,27 @@
"cells": [
{
"cell_type": "code",
"execution_count": 34,
"execution_count": 2,
"metadata": {},
"outputs": [],
"outputs": [
{
"ename": "OSError",
"evalue": "Cannot save file into a non-existent directory: 'results_01'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mOSError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[2], line 71\u001b[0m\n\u001b[1;32m 69\u001b[0m \u001b[38;5;66;03m# Create a DataFrame from the results\u001b[39;00m\n\u001b[1;32m 70\u001b[0m df \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mDataFrame(results)\n\u001b[0;32m---> 71\u001b[0m \u001b[43mdf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_csv\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m./results_01/\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mrate\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m_\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mdataset\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m_results.csv\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindex\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/data/linglong/.conda/envs/pypots/lib/python3.10/site-packages/pandas/util/_decorators.py:333\u001b[0m, in \u001b[0;36mdeprecate_nonkeyword_arguments.<locals>.decorate.<locals>.wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 327\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(args) \u001b[38;5;241m>\u001b[39m num_allow_args:\n\u001b[1;32m 328\u001b[0m warnings\u001b[38;5;241m.\u001b[39mwarn(\n\u001b[1;32m 329\u001b[0m msg\u001b[38;5;241m.\u001b[39mformat(arguments\u001b[38;5;241m=\u001b[39m_format_argument_list(allow_args)),\n\u001b[1;32m 330\u001b[0m \u001b[38;5;167;01mFutureWarning\u001b[39;00m,\n\u001b[1;32m 331\u001b[0m stacklevel\u001b[38;5;241m=\u001b[39mfind_stack_level(),\n\u001b[1;32m 332\u001b[0m )\n\u001b[0;32m--> 333\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/data/linglong/.conda/envs/pypots/lib/python3.10/site-packages/pandas/core/generic.py:3964\u001b[0m, in \u001b[0;36mNDFrame.to_csv\u001b[0;34m(self, path_or_buf, sep, na_rep, float_format, columns, header, index, index_label, mode, encoding, compression, quoting, quotechar, lineterminator, chunksize, date_format, doublequote, escapechar, decimal, errors, storage_options)\u001b[0m\n\u001b[1;32m 3953\u001b[0m df \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28mself\u001b[39m, ABCDataFrame) \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mto_frame()\n\u001b[1;32m 3955\u001b[0m formatter \u001b[38;5;241m=\u001b[39m DataFrameFormatter(\n\u001b[1;32m 3956\u001b[0m frame\u001b[38;5;241m=\u001b[39mdf,\n\u001b[1;32m 3957\u001b[0m header\u001b[38;5;241m=\u001b[39mheader,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 3961\u001b[0m decimal\u001b[38;5;241m=\u001b[39mdecimal,\n\u001b[1;32m 3962\u001b[0m )\n\u001b[0;32m-> 3964\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mDataFrameRenderer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mformatter\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_csv\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 3965\u001b[0m \u001b[43m \u001b[49m\u001b[43mpath_or_buf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3966\u001b[0m \u001b[43m \u001b[49m\u001b[43mlineterminator\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlineterminator\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3967\u001b[0m \u001b[43m \u001b[49m\u001b[43msep\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msep\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3968\u001b[0m \u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3969\u001b[0m \u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3970\u001b[0m \u001b[43m \u001b[49m\u001b[43mcompression\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcompression\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3971\u001b[0m \u001b[43m \u001b[49m\u001b[43mquoting\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mquoting\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3972\u001b[0m \u001b[43m \u001b[49m\u001b[43mcolumns\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcolumns\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3973\u001b[0m \u001b[43m \u001b[49m\u001b[43mindex_label\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mindex_label\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3974\u001b[0m \u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3975\u001b[0m \u001b[43m \u001b[49m\u001b[43mchunksize\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchunksize\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3976\u001b[0m \u001b[43m \u001b[49m\u001b[43mquotechar\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mquotechar\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3977\u001b[0m \u001b[43m \u001b[49m\u001b[43mdate_format\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdate_format\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3978\u001b[0m \u001b[43m \u001b[49m\u001b[43mdoublequote\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdoublequote\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3979\u001b[0m \u001b[43m \u001b[49m\u001b[43mescapechar\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mescapechar\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3980\u001b[0m \u001b[43m \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstorage_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3981\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/data/linglong/.conda/envs/pypots/lib/python3.10/site-packages/pandas/io/formats/format.py:1014\u001b[0m, in \u001b[0;36mDataFrameRenderer.to_csv\u001b[0;34m(self, path_or_buf, encoding, sep, columns, index_label, mode, compression, quoting, quotechar, lineterminator, chunksize, date_format, doublequote, escapechar, errors, storage_options)\u001b[0m\n\u001b[1;32m 993\u001b[0m created_buffer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 995\u001b[0m csv_formatter \u001b[38;5;241m=\u001b[39m CSVFormatter(\n\u001b[1;32m 996\u001b[0m path_or_buf\u001b[38;5;241m=\u001b[39mpath_or_buf,\n\u001b[1;32m 997\u001b[0m lineterminator\u001b[38;5;241m=\u001b[39mlineterminator,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1012\u001b[0m formatter\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfmt,\n\u001b[1;32m 1013\u001b[0m )\n\u001b[0;32m-> 1014\u001b[0m \u001b[43mcsv_formatter\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msave\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1016\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m created_buffer:\n\u001b[1;32m 1017\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(path_or_buf, StringIO)\n",
"File \u001b[0;32m~/data/linglong/.conda/envs/pypots/lib/python3.10/site-packages/pandas/io/formats/csvs.py:251\u001b[0m, in \u001b[0;36mCSVFormatter.save\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 247\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 248\u001b[0m \u001b[38;5;124;03mCreate the writer & save.\u001b[39;00m\n\u001b[1;32m 249\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 250\u001b[0m \u001b[38;5;66;03m# apply compression and byte/text conversion\u001b[39;00m\n\u001b[0;32m--> 251\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[43mget_handle\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 252\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfilepath_or_buffer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 253\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 254\u001b[0m \u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 255\u001b[0m \u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 256\u001b[0m \u001b[43m \u001b[49m\u001b[43mcompression\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcompression\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 257\u001b[0m \u001b[43m \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstorage_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 258\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m handles:\n\u001b[1;32m 259\u001b[0m \u001b[38;5;66;03m# Note: self.encoding is irrelevant here\u001b[39;00m\n\u001b[1;32m 260\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mwriter \u001b[38;5;241m=\u001b[39m csvlib\u001b[38;5;241m.\u001b[39mwriter(\n\u001b[1;32m 261\u001b[0m handles\u001b[38;5;241m.\u001b[39mhandle,\n\u001b[1;32m 262\u001b[0m lineterminator\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlineterminator,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 267\u001b[0m quotechar\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mquotechar,\n\u001b[1;32m 268\u001b[0m )\n\u001b[1;32m 270\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_save()\n",
"File \u001b[0;32m~/data/linglong/.conda/envs/pypots/lib/python3.10/site-packages/pandas/io/common.py:749\u001b[0m, in \u001b[0;36mget_handle\u001b[0;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[1;32m 747\u001b[0m \u001b[38;5;66;03m# Only for write methods\u001b[39;00m\n\u001b[1;32m 748\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m mode \u001b[38;5;129;01mand\u001b[39;00m is_path:\n\u001b[0;32m--> 749\u001b[0m \u001b[43mcheck_parent_directory\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mhandle\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 751\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m compression:\n\u001b[1;32m 752\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m compression \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mzstd\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m 753\u001b[0m \u001b[38;5;66;03m# compression libraries do not like an explicit text-mode\u001b[39;00m\n",
"File \u001b[0;32m~/data/linglong/.conda/envs/pypots/lib/python3.10/site-packages/pandas/io/common.py:616\u001b[0m, in \u001b[0;36mcheck_parent_directory\u001b[0;34m(path)\u001b[0m\n\u001b[1;32m 614\u001b[0m parent \u001b[38;5;241m=\u001b[39m Path(path)\u001b[38;5;241m.\u001b[39mparent\n\u001b[1;32m 615\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m parent\u001b[38;5;241m.\u001b[39mis_dir():\n\u001b[0;32m--> 616\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m(\u001b[38;5;124mrf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCannot save file into a non-existent directory: \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
"\u001b[0;31mOSError\u001b[0m: Cannot save file into a non-existent directory: 'results_01'"
]
}
],
"source": [
"import os\n",
"import re\n",
Expand Down Expand Up @@ -110,7 +128,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.1.undefined"
"version": "3.10.13"
}
},
"nbformat": 4,
Expand Down
10 changes: 10 additions & 0 deletions .../results_process/classification_log/Pedestrian_point_rate01_log/Autoformer_Pedestrian.log
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2024-06-09 20:52:47 [INFO]: Have set the random seed as 2024 for numpy and pytorch.
2024-06-09 20:55:08 [INFO]: Have set the random seed as 2025 for numpy and pytorch.
2024-06-09 20:56:50 [INFO]: Have set the random seed as 2026 for numpy and pytorch.
2024-06-09 20:58:47 [INFO]: Have set the random seed as 2027 for numpy and pytorch.
2024-06-09 21:00:46 [INFO]: Have set the random seed as 2028 for numpy and pytorch.
2024-06-09 21:01:45 [INFO]:
XGB without imputation PR_AUC: 0.9724±0.0000, ROC_AUC: 0.9957±0.0000
XGB with Autoformer imputation PR_AUC: 0.9779±0.0000, ROC_AUC: 0.9964±0.0000
RNN with Autoformer imputation PR_AUC: 0.4804±0.0856, ROC_AUC: 0.8979±0.0255
Transformer with Autoformer imputation PR_AUC: 0.9318±0.0273, ROC_AUC: 0.9890±0.0039
10 changes: 10 additions & 0 deletions ..._code/results_process/classification_log/Pedestrian_point_rate01_log/BRITS_Pedestrian.log
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2024-06-09 20:52:47 [INFO]: Have set the random seed as 2024 for numpy and pytorch.
2024-06-09 20:54:40 [INFO]: Have set the random seed as 2025 for numpy and pytorch.
2024-06-09 20:56:34 [INFO]: Have set the random seed as 2026 for numpy and pytorch.
2024-06-09 20:58:23 [INFO]: Have set the random seed as 2027 for numpy and pytorch.
2024-06-09 20:59:49 [INFO]: Have set the random seed as 2028 for numpy and pytorch.
2024-06-09 21:01:17 [INFO]:
XGB without imputation PR_AUC: 0.9724±0.0000, ROC_AUC: 0.9957±0.0000
XGB with BRITS imputation PR_AUC: 0.9809±0.0000, ROC_AUC: 0.9969±0.0000
RNN with BRITS imputation PR_AUC: 0.4622±0.0511, ROC_AUC: 0.8980±0.0167
Transformer with BRITS imputation PR_AUC: 0.9384±0.0266, ROC_AUC: 0.9906±0.0037
10 changes: 10 additions & 0 deletions ...k_code/results_process/classification_log/Pedestrian_point_rate01_log/CSDI_Pedestrian.log
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2024-06-09 20:52:47 [INFO]: Have set the random seed as 2024 for numpy and pytorch.
2024-06-09 20:54:20 [INFO]: Have set the random seed as 2025 for numpy and pytorch.
2024-06-09 20:56:11 [INFO]: Have set the random seed as 2026 for numpy and pytorch.
2024-06-09 20:57:59 [INFO]: Have set the random seed as 2027 for numpy and pytorch.
2024-06-09 20:59:46 [INFO]: Have set the random seed as 2028 for numpy and pytorch.
2024-06-09 21:01:39 [INFO]:
XGB without imputation PR_AUC: 0.9724±0.0000, ROC_AUC: 0.9957±0.0000
XGB with CSDI imputation PR_AUC: 0.9776±0.0000, ROC_AUC: 0.9964±0.0000
RNN with CSDI imputation PR_AUC: 0.5107±0.0484, ROC_AUC: 0.9071±0.0187
Transformer with CSDI imputation PR_AUC: 0.9244±0.0286, ROC_AUC: 0.9887±0.0039
10 changes: 10 additions & 0 deletions ...results_process/classification_log/Pedestrian_point_rate01_log/Crossformer_Pedestrian.log
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2024-06-09 20:52:47 [INFO]: Have set the random seed as 2024 for numpy and pytorch.
2024-06-09 20:54:30 [INFO]: Have set the random seed as 2025 for numpy and pytorch.
2024-06-09 20:56:11 [INFO]: Have set the random seed as 2026 for numpy and pytorch.
2024-06-09 20:57:57 [INFO]: Have set the random seed as 2027 for numpy and pytorch.
2024-06-09 20:59:42 [INFO]: Have set the random seed as 2028 for numpy and pytorch.
2024-06-09 21:01:34 [INFO]:
XGB without imputation PR_AUC: 0.9724±0.0000, ROC_AUC: 0.9957±0.0000
XGB with Crossformer imputation PR_AUC: 0.9803±0.0000, ROC_AUC: 0.9969±0.0000
RNN with Crossformer imputation PR_AUC: 0.5090±0.0539, ROC_AUC: 0.9075±0.0164
Transformer with Crossformer imputation PR_AUC: 0.9230±0.0365, ROC_AUC: 0.9889±0.0051
10 changes: 10 additions & 0 deletions ...ode/results_process/classification_log/Pedestrian_point_rate01_log/DLinear_Pedestrian.log
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2024-06-09 20:52:47 [INFO]: Have set the random seed as 2024 for numpy and pytorch.
2024-06-09 20:54:18 [INFO]: Have set the random seed as 2025 for numpy and pytorch.
2024-06-09 20:56:09 [INFO]: Have set the random seed as 2026 for numpy and pytorch.
2024-06-09 20:57:57 [INFO]: Have set the random seed as 2027 for numpy and pytorch.
2024-06-09 20:59:45 [INFO]: Have set the random seed as 2028 for numpy and pytorch.
2024-06-09 21:01:21 [INFO]:
XGB without imputation PR_AUC: 0.9724±0.0000, ROC_AUC: 0.9957±0.0000
XGB with DLinear imputation PR_AUC: 0.9808±0.0000, ROC_AUC: 0.9971±0.0000
RNN with DLinear imputation PR_AUC: 0.5202±0.0536, ROC_AUC: 0.9118±0.0157
Transformer with DLinear imputation PR_AUC: 0.9036±0.0289, ROC_AUC: 0.9858±0.0038
10 changes: 10 additions & 0 deletions ...e/results_process/classification_log/Pedestrian_point_rate01_log/ETSformer_Pedestrian.log
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2024-06-09 20:52:47 [INFO]: Have set the random seed as 2024 for numpy and pytorch.
2024-06-09 20:54:28 [INFO]: Have set the random seed as 2025 for numpy and pytorch.
2024-06-09 20:56:10 [INFO]: Have set the random seed as 2026 for numpy and pytorch.
2024-06-09 20:58:06 [INFO]: Have set the random seed as 2027 for numpy and pytorch.
2024-06-09 20:59:50 [INFO]: Have set the random seed as 2028 for numpy and pytorch.
2024-06-09 21:01:30 [INFO]:
XGB without imputation PR_AUC: 0.9724±0.0000, ROC_AUC: 0.9957±0.0000
XGB with ETSformer imputation PR_AUC: 0.9765±0.0000, ROC_AUC: 0.9963±0.0000
RNN with ETSformer imputation PR_AUC: 0.4870±0.0567, ROC_AUC: 0.9009±0.0200
Transformer with ETSformer imputation PR_AUC: 0.9101±0.0354, ROC_AUC: 0.9861±0.0052
10 changes: 10 additions & 0 deletions ...k_code/results_process/classification_log/Pedestrian_point_rate01_log/FiLM_Pedestrian.log
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2024-06-09 20:52:47 [INFO]: Have set the random seed as 2024 for numpy and pytorch.
2024-06-09 20:54:42 [INFO]: Have set the random seed as 2025 for numpy and pytorch.
2024-06-09 20:56:49 [INFO]: Have set the random seed as 2026 for numpy and pytorch.
2024-06-09 20:58:53 [INFO]: Have set the random seed as 2027 for numpy and pytorch.
2024-06-09 21:00:41 [INFO]: Have set the random seed as 2028 for numpy and pytorch.
2024-06-09 21:01:46 [INFO]:
XGB without imputation PR_AUC: 0.9724±0.0000, ROC_AUC: 0.9957±0.0000
XGB with FiLM imputation PR_AUC: 0.9731±0.0000, ROC_AUC: 0.9958±0.0000
RNN with FiLM imputation PR_AUC: 0.4823±0.0200, ROC_AUC: 0.9035±0.0075
Transformer with FiLM imputation PR_AUC: 0.9554±0.0075, ROC_AUC: 0.9923±0.0013
10 changes: 10 additions & 0 deletions ..._code/results_process/classification_log/Pedestrian_point_rate01_log/FreTS_Pedestrian.log
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2024-06-09 20:52:47 [INFO]: Have set the random seed as 2024 for numpy and pytorch.
2024-06-09 20:54:30 [INFO]: Have set the random seed as 2025 for numpy and pytorch.
2024-06-09 20:56:35 [INFO]: Have set the random seed as 2026 for numpy and pytorch.
2024-06-09 20:58:11 [INFO]: Have set the random seed as 2027 for numpy and pytorch.
2024-06-09 20:59:38 [INFO]: Have set the random seed as 2028 for numpy and pytorch.
2024-06-09 21:01:23 [INFO]:
XGB without imputation PR_AUC: 0.9724±0.0000, ROC_AUC: 0.9957±0.0000
XGB with FreTS imputation PR_AUC: 0.9817±0.0000, ROC_AUC: 0.9971±0.0000
RNN with FreTS imputation PR_AUC: 0.4738±0.0627, ROC_AUC: 0.8955±0.0230
Transformer with FreTS imputation PR_AUC: 0.9025±0.0278, ROC_AUC: 0.9850±0.0039
10 changes: 10 additions & 0 deletions ..._code/results_process/classification_log/Pedestrian_point_rate01_log/GPVAE_Pedestrian.log
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2024-06-09 20:51:25 [INFO]: Have set the random seed as 2024 for numpy and pytorch.
2024-06-09 20:54:22 [INFO]: Have set the random seed as 2025 for numpy and pytorch.
2024-06-09 20:56:23 [INFO]: Have set the random seed as 2026 for numpy and pytorch.
2024-06-09 20:58:32 [INFO]: Have set the random seed as 2027 for numpy and pytorch.
2024-06-09 21:00:35 [INFO]: Have set the random seed as 2028 for numpy and pytorch.
2024-06-09 21:02:22 [INFO]:
XGB without imputation PR_AUC: 0.9724±0.0000, ROC_AUC: 0.9957±0.0000
XGB with GPVAE imputation PR_AUC: 0.9735±0.0000, ROC_AUC: 0.9960±0.0000
RNN with GPVAE imputation PR_AUC: 0.4723±0.0645, ROC_AUC: 0.8932±0.0202
Transformer with GPVAE imputation PR_AUC: 0.8979±0.0033, ROC_AUC: 0.9850±0.0010
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