autox/autox_server/demo/bank/bank_test.ipynb

{
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     "start_time": "2022-01-07T08:40:11.481389Z"
    },
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    {
     "name": "stderr",
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     "text": [
      "/home/caihengxing/anaconda3/lib/python3.7/site-packages/pandas/compat/_optional.py:138: UserWarning: Pandas requires version '2.7.0' or newer of 'numexpr' (version '2.6.9' currently installed).\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    }
   ],
   "source": [
    "from autox import AutoXServer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-07T08:40:17.470294Z",
     "start_time": "2022-01-07T08:40:15.414792Z"
    }
   },
   "outputs": [],
   "source": [
    "autoxserver = AutoXServer(is_train = False, server_name = 'bank') # 注意server_name需要和训练时一致\n",
    "\n",
    "save_path = './save'\n",
    "autoxserver.load_server(save_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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    },
    "scrolled": true
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   "outputs": [
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     "name": "stderr",
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     "text": [
      "   INFO ->  *** phase: test\n",
      "   INFO ->  *** phase: test\n",
      "   INFO ->  key = overdue, shape = (44476, 4)\n",
      "   INFO ->  key = overdue, shape = (44476, 4)\n",
      "   INFO ->  key = userinfo, shape = (44476, 6)\n",
      "   INFO ->  key = userinfo, shape = (44476, 6)\n",
      "   INFO ->  key = bank, shape = (4791888, 9)\n",
      "   INFO ->  key = bank, shape = (4791888, 9)\n",
      "   INFO ->  key = browse, shape = (18410808, 7)\n",
      "   INFO ->  key = browse, shape = (18410808, 7)\n",
      "   INFO ->  key = bill, shape = (1873185, 29)\n",
      "   INFO ->  key = bill, shape = (1873185, 29)\n",
      "   INFO ->  remain_time: 9999999995.04063 s\n",
      "   INFO ->  remain_time: 9999999995.04063 s\n",
      "   INFO ->  [+] preprocess, delete_row\n",
      "   INFO ->  [+] preprocess, delete_row\n",
      "   INFO ->  [+] preprocess, parsing_time\n",
      "   INFO ->  [+] preprocess, parsing_time\n",
      "   INFO ->  time columns: {}\n",
      "   INFO ->  time columns: {}\n",
      "   INFO ->  remain_time: 9999999995.036678 s\n",
      "   INFO ->  remain_time: 9999999995.036678 s\n",
      "   INFO ->  [+] join simple tables\n",
      "   INFO ->  [+] join simple tables\n",
      "   INFO ->  userinfo\n",
      "   INFO ->  userinfo\n",
      "   INFO ->  remain_time: 9999999994.99544 s\n",
      "   INFO ->  remain_time: 9999999994.99544 s\n",
      "   INFO ->  [+] preprocess_2\n",
      "   INFO ->  [+] preprocess_2\n",
      "   INFO ->  [+] preprocess_2: del invalid features\n",
      "   INFO ->  [+] preprocess_2: del invalid features\n",
      "   INFO ->  remain_time: 9999999994.99096 s\n",
      "   INFO ->  remain_time: 9999999994.99096 s\n",
      "   INFO ->  [+] join indirect 1_to_M tables\n",
      "   INFO ->  [+] join indirect 1_to_M tables\n",
      "   INFO ->  remain_time: 9999999994.990957 s\n",
      "   INFO ->  remain_time: 9999999994.990957 s\n",
      "   INFO ->  [+] preprocess_after_join_indirect_tables\n",
      "   INFO ->  [+] preprocess_after_join_indirect_tables\n",
      "   INFO ->  [+] preprocess_after_join_indirect_tables: rename columns\n",
      "   INFO ->  [+] preprocess_after_join_indirect_tables: rename columns\n",
      "   INFO ->  remain_time: 9999999994.988434 s\n",
      "   INFO ->  remain_time: 9999999994.988434 s\n",
      "   INFO ->  [+] join 1_to_M tables\n",
      "   INFO ->  [+] join 1_to_M tables\n",
      "   INFO ->  process table : bank\n",
      "   INFO ->  process table : bank\n",
      "   INFO ->  process table : browse\n",
      "   INFO ->  process table : browse\n",
      "   INFO ->  process table : bill\n",
      "   INFO ->  process table : bill\n",
      "   INFO ->  remain_time: 9999999979.852364 s\n",
      "   INFO ->  remain_time: 9999999979.852364 s\n",
      "   INFO ->  [+] preprocess_3\n",
      "   INFO ->  [+] preprocess_3\n",
      "   INFO ->  [+] preprocess_3: rename columns\n",
      "   INFO ->  [+] preprocess_3: rename columns\n",
      "   INFO ->  [+] preprocess_3: del invalid features\n",
      "   INFO ->  [+] preprocess_3: del invalid features\n",
      "   INFO ->  [+] preprocess_3: process multi_value features\n",
      "   INFO ->  [+] preprocess_3: process multi_value features\n",
      "   INFO ->  [+] preprocess_3: label encoding\n",
      "   INFO ->  [+] preprocess_3: label encoding\n",
      "   INFO ->  remain_time: 9999999979.687836 s\n",
      "   INFO ->  remain_time: 9999999979.687836 s\n",
      "   INFO ->  [+] base_lgb lightgbm\n",
      "   INFO ->  [+] base_lgb lightgbm\n",
      "   INFO ->  remain_time: 9999999979.567106 s\n",
      "   INFO ->  remain_time: 9999999979.567106 s\n",
      "   INFO ->  [+] feature engineer, generate_concat\n",
      "   INFO ->  [+] feature engineer, generate_concat\n",
      "   INFO ->  remain_time: 9999999979.566154 s\n",
      "   INFO ->  remain_time: 9999999979.566154 s\n",
      "   INFO ->  [+] feature engineer, onehot\n",
      "   INFO ->  [+] feature engineer, onehot\n",
      "   INFO ->  onehot features: []\n",
      "   INFO ->  onehot features: []\n",
      "   INFO ->  remain_time: 9999999979.563116 s\n",
      "   INFO ->  remain_time: 9999999979.563116 s\n",
      "   INFO ->  [+] feature engineer, count\n",
      "   INFO ->  [+] feature engineer, count\n",
      "   INFO ->  remain_time: 9999999979.558277 s\n",
      "   INFO ->  remain_time: 9999999979.558277 s\n",
      "   INFO ->  [+] feature engineer, shift\n",
      "   INFO ->  [+] feature engineer, shift\n",
      "   INFO ->  remain_time: 9999999979.46902 s\n",
      "   INFO ->  remain_time: 9999999979.46902 s\n",
      "   INFO ->  [+] feature engineer, time_diff\n",
      "   INFO ->  [+] feature engineer, time_diff\n",
      "   INFO ->  big_cols_Unix_timestamp: ['flag1']\n",
      "   INFO ->  big_cols_Unix_timestamp: ['flag1']\n",
      "   INFO ->  big_cols_datetime: []\n",
      "   INFO ->  big_cols_datetime: []\n",
      "100%|██████████| 1/1 [00:00<00:00,  3.12it/s]\n",
      "   INFO ->  remain_time: 9999999979.141363 s\n",
      "   INFO ->  remain_time: 9999999979.141363 s\n",
      "   INFO ->  [+] merge_table\n",
      "   INFO ->  [+] merge_table\n",
      "   INFO ->  shape of BIG: (44476, 216)\n",
      "   INFO ->  shape of BIG: (44476, 216)\n",
      "   INFO ->  shape of FE_onehot: (44476, 0)\n",
      "   INFO ->  shape of FE_onehot: (44476, 0)\n",
      "   INFO ->  shape of FE_count: (44476, 0)\n",
      "   INFO ->  shape of FE_count: (44476, 0)\n",
      "   INFO ->  shape of FE_shift: (0, 0)\n",
      "   INFO ->  shape of FE_shift: (0, 0)\n",
      "   INFO ->  shape of FE_cat_time_diff: (44476, 0)\n",
      "   INFO ->  shape of FE_cat_time_diff: (44476, 0)\n",
      "   INFO ->  shape after fe: (44476, 216)\n",
      "   INFO ->  shape after fe: (44476, 216)\n",
      "   INFO ->  remain_time: 9999999978.773258 s\n",
      "   INFO ->  remain_time: 9999999978.773258 s\n",
      "   INFO ->  [+] fe_lgb lightgbm\n",
      "   INFO ->  [+] fe_lgb lightgbm\n",
      "   INFO ->  remain_time: 9999999978.54987 s\n",
      "   INFO ->  remain_time: 9999999978.54987 s\n",
      "   INFO ->  remain_time: 9999999978.442007 s\n",
      "   INFO ->  remain_time: 9999999978.442007 s\n",
      "   INFO ->  remain_time: 9999999978.440344 s\n",
      "   INFO ->  remain_time: 9999999978.440344 s\n"
     ]
    }
   ],
   "source": [
    "test_set_path = './bank/test_data'\n",
    "pred = autoxserver.predict(test_set_path = test_set_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
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     "end_time": "2022-01-07T08:40:39.100472Z",
     "start_time": "2022-01-07T08:40:39.089531Z"
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   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(8645, 2)\n"
     ]
    },
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       "                        new_user_id     label\n",
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     },
     "execution_count": 4,
     "metadata": {},
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   ],
   "source": [
    "print(pred.shape)\n",
    "pred.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-07T08:40:39.122304Z",
     "start_time": "2022-01-07T08:40:39.102196Z"
    },
    "scrolled": false
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6990700220969959"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn.metrics import roc_auc_score\n",
    "\n",
    "solution = pd.read_csv('./bank/solution.csv')\n",
    "roc_auc_score(solution['label'], pred['label'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
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     "start_time": "2022-01-07T08:40:51.639811Z"
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       "                        new_user_id  label\n",
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   ],
   "source": [
    "solution.head()"
   ]
  },
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   "execution_count": null,
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   "source": []
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