experiments/weekly-customs-selection/weekly-custom-selection-results.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Weekly Custom Selection by DATE and its Comparison with Other Algorithms\n",
    "\n",
    "In this script, we compared the prediction results of XGB, XGB+LR, DATE_CLS, and DATE_REV model. <br>Customs administrations will run DATE daily, or weekly, and select highly-fraudulent transactions to inspect."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.max_columns', 50)\n",
    "pd.set_option('display.max_rows', 50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Weekly import data (For safety concern, full data is not uploaded in our repository)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = pd.read_csv('./weekly-data/week1_ano.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2124"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['SGD_NUM', 'SGD_DATE', 'RECEIPT_NUM', 'IMPORTER_TIN', 'IMPORTER_NAME',\n",
       "       'DECLARANT_CODE', 'DECLARANT_NAME', 'OFFICE_CODE', 'ORIGIN_CODE',\n",
       "       'HSCODE', 'ITM_NUM', 'INITIAL_ITM_QTY', 'INITIAL_ITM_WEIGHT',\n",
       "       'INITIAL_ITM_FOB', 'INITIAL_ITM_CIF', 'INITIAL_ITM_TOTAL_TAX',\n",
       "       'INITIAL_TOTAL_TAX', 'key_identifier'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SGD_NUM</th>\n",
       "      <th>SGD_DATE</th>\n",
       "      <th>RECEIPT_NUM</th>\n",
       "      <th>IMPORTER_TIN</th>\n",
       "      <th>IMPORTER_NAME</th>\n",
       "      <th>DECLARANT_CODE</th>\n",
       "      <th>DECLARANT_NAME</th>\n",
       "      <th>OFFICE_CODE</th>\n",
       "      <th>ORIGIN_CODE</th>\n",
       "      <th>HSCODE</th>\n",
       "      <th>ITM_NUM</th>\n",
       "      <th>INITIAL_ITM_QTY</th>\n",
       "      <th>INITIAL_ITM_WEIGHT</th>\n",
       "      <th>INITIAL_ITM_FOB</th>\n",
       "      <th>INITIAL_ITM_CIF</th>\n",
       "      <th>INITIAL_ITM_TOTAL_TAX</th>\n",
       "      <th>INITIAL_TOTAL_TAX</th>\n",
       "      <th>key_identifier</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>C12861</td>\n",
       "      <td>2020-04-18T00:00:00Z</td>\n",
       "      <td>R14335</td>\n",
       "      <td>IMPW2166</td>\n",
       "      <td>IMPNAMEW2226</td>\n",
       "      <td>DEC6463</td>\n",
       "      <td>IMPW129</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY277</td>\n",
       "      <td>2621900000</td>\n",
       "      <td>43831</td>\n",
       "      <td>91</td>\n",
       "      <td>182273.00</td>\n",
       "      <td>3025932</td>\n",
       "      <td>8776321</td>\n",
       "      <td>1242677</td>\n",
       "      <td>1242677</td>\n",
       "      <td>C12861_2020-04-18_OFFICE92_43831_2621900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>C12862</td>\n",
       "      <td>2020-04-18T00:00:00Z</td>\n",
       "      <td>R14334</td>\n",
       "      <td>IMPW2166</td>\n",
       "      <td>IMPNAMEW2226</td>\n",
       "      <td>DEC6463</td>\n",
       "      <td>IMPW129</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY277</td>\n",
       "      <td>8205100000</td>\n",
       "      <td>43862</td>\n",
       "      <td>5</td>\n",
       "      <td>1521.00</td>\n",
       "      <td>8775209</td>\n",
       "      <td>9505047</td>\n",
       "      <td>1951623</td>\n",
       "      <td>2184755</td>\n",
       "      <td>C12862_2020-04-18_OFFICE92_43862_8205100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C12862</td>\n",
       "      <td>2020-04-18T00:00:00Z</td>\n",
       "      <td>R14334</td>\n",
       "      <td>IMPW2166</td>\n",
       "      <td>IMPNAMEW2226</td>\n",
       "      <td>DEC6463</td>\n",
       "      <td>IMPW129</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY277</td>\n",
       "      <td>8465990000</td>\n",
       "      <td>43863</td>\n",
       "      <td>5</td>\n",
       "      <td>1521.00</td>\n",
       "      <td>3177522</td>\n",
       "      <td>3441975</td>\n",
       "      <td>233132</td>\n",
       "      <td>2184755</td>\n",
       "      <td>C12862_2020-04-18_OFFICE92_43863_8465990000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>C12865</td>\n",
       "      <td>2020-04-18T00:00:00Z</td>\n",
       "      <td>R14045</td>\n",
       "      <td>IMP323400</td>\n",
       "      <td>IMPNAMEW7157</td>\n",
       "      <td>DEC8458</td>\n",
       "      <td>DECNAMEW388</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY759</td>\n",
       "      <td>8484100000</td>\n",
       "      <td>43922</td>\n",
       "      <td>6</td>\n",
       "      <td>334.25</td>\n",
       "      <td>6371047</td>\n",
       "      <td>6371047</td>\n",
       "      <td>85471</td>\n",
       "      <td>508254</td>\n",
       "      <td>C12865_2020-04-18_OFFICE92_43922_8484100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>C12865</td>\n",
       "      <td>2020-04-18T00:00:00Z</td>\n",
       "      <td>R14045</td>\n",
       "      <td>IMP323400</td>\n",
       "      <td>IMPNAMEW7157</td>\n",
       "      <td>DEC8458</td>\n",
       "      <td>DECNAMEW388</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY759</td>\n",
       "      <td>7318190000</td>\n",
       "      <td>43925</td>\n",
       "      <td>5</td>\n",
       "      <td>334.25</td>\n",
       "      <td>6371047</td>\n",
       "      <td>6371047</td>\n",
       "      <td>65120</td>\n",
       "      <td>508254</td>\n",
       "      <td>C12865_2020-04-18_OFFICE92_43925_7318190000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  SGD_NUM              SGD_DATE RECEIPT_NUM IMPORTER_TIN IMPORTER_NAME  \\\n",
       "0  C12861  2020-04-18T00:00:00Z      R14335     IMPW2166  IMPNAMEW2226   \n",
       "1  C12862  2020-04-18T00:00:00Z      R14334     IMPW2166  IMPNAMEW2226   \n",
       "2  C12862  2020-04-18T00:00:00Z      R14334     IMPW2166  IMPNAMEW2226   \n",
       "3  C12865  2020-04-18T00:00:00Z      R14045    IMP323400  IMPNAMEW7157   \n",
       "4  C12865  2020-04-18T00:00:00Z      R14045    IMP323400  IMPNAMEW7157   \n",
       "\n",
       "  DECLARANT_CODE DECLARANT_NAME OFFICE_CODE ORIGIN_CODE      HSCODE ITM_NUM  \\\n",
       "0        DEC6463        IMPW129    OFFICE92    CNTRY277  2621900000   43831   \n",
       "1        DEC6463        IMPW129    OFFICE92    CNTRY277  8205100000   43862   \n",
       "2        DEC6463        IMPW129    OFFICE92    CNTRY277  8465990000   43863   \n",
       "3        DEC8458    DECNAMEW388    OFFICE92    CNTRY759  8484100000   43922   \n",
       "4        DEC8458    DECNAMEW388    OFFICE92    CNTRY759  7318190000   43925   \n",
       "\n",
       "   INITIAL_ITM_QTY  INITIAL_ITM_WEIGHT  INITIAL_ITM_FOB  INITIAL_ITM_CIF  \\\n",
       "0               91           182273.00          3025932          8776321   \n",
       "1                5             1521.00          8775209          9505047   \n",
       "2                5             1521.00          3177522          3441975   \n",
       "3                6              334.25          6371047          6371047   \n",
       "4                5              334.25          6371047          6371047   \n",
       "\n",
       "   INITIAL_ITM_TOTAL_TAX  INITIAL_TOTAL_TAX  \\\n",
       "0                1242677            1242677   \n",
       "1                1951623            2184755   \n",
       "2                 233132            2184755   \n",
       "3                  85471             508254   \n",
       "4                  65120             508254   \n",
       "\n",
       "                                key_identifier  \n",
       "0  C12861_2020-04-18_OFFICE92_43831_2621900000  \n",
       "1  C12862_2020-04-18_OFFICE92_43862_8205100000  \n",
       "2  C12862_2020-04-18_OFFICE92_43863_8465990000  \n",
       "3  C12865_2020-04-18_OFFICE92_43922_8484100000  \n",
       "4  C12865_2020-04-18_OFFICE92_43925_7318190000  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Weekly import data with prediction results (For safety concern, full data is not uploaded in our repository)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df3 = pd.read_csv('./weekly-data/week1_ano_result.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SGD_NUM</th>\n",
       "      <th>SGD_DATE</th>\n",
       "      <th>IMPORTER_TIN</th>\n",
       "      <th>DECLARANT_CODE</th>\n",
       "      <th>OFFICE_CODE</th>\n",
       "      <th>ORIGIN_CODE</th>\n",
       "      <th>HSCODE</th>\n",
       "      <th>ITM_NUM</th>\n",
       "      <th>XGB</th>\n",
       "      <th>Ranking-XGB</th>\n",
       "      <th>XGB+LR</th>\n",
       "      <th>Ranking-XGB+LR</th>\n",
       "      <th>DATE_CLS</th>\n",
       "      <th>Ranking-DATE_CLS</th>\n",
       "      <th>DATE_REV</th>\n",
       "      <th>Ranking-DATE_REV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>C12861</td>\n",
       "      <td>2020-04-18T00:00:00Z</td>\n",
       "      <td>IMPW2166</td>\n",
       "      <td>DEC6463</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY277</td>\n",
       "      <td>2621900000</td>\n",
       "      <td>43831</td>\n",
       "      <td>0.007388</td>\n",
       "      <td>759</td>\n",
       "      <td>0.073774</td>\n",
       "      <td>359</td>\n",
       "      <td>0.019338</td>\n",
       "      <td>357</td>\n",
       "      <td>0.006783</td>\n",
       "      <td>293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>C12862</td>\n",
       "      <td>2020-04-18T00:00:00Z</td>\n",
       "      <td>IMPW2166</td>\n",
       "      <td>DEC6463</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY277</td>\n",
       "      <td>8205100000</td>\n",
       "      <td>43862</td>\n",
       "      <td>0.019617</td>\n",
       "      <td>367</td>\n",
       "      <td>0.120060</td>\n",
       "      <td>317</td>\n",
       "      <td>0.046201</td>\n",
       "      <td>280</td>\n",
       "      <td>0.021700</td>\n",
       "      <td>264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C12862</td>\n",
       "      <td>2020-04-18T00:00:00Z</td>\n",
       "      <td>IMPW2166</td>\n",
       "      <td>DEC6463</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY277</td>\n",
       "      <td>8465990000</td>\n",
       "      <td>43863</td>\n",
       "      <td>0.003430</td>\n",
       "      <td>958</td>\n",
       "      <td>0.001457</td>\n",
       "      <td>815</td>\n",
       "      <td>0.000113</td>\n",
       "      <td>1868</td>\n",
       "      <td>-0.012125</td>\n",
       "      <td>2047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>C12865</td>\n",
       "      <td>2020-04-18T00:00:00Z</td>\n",
       "      <td>IMP323400</td>\n",
       "      <td>DEC8458</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY759</td>\n",
       "      <td>8484100000</td>\n",
       "      <td>43922</td>\n",
       "      <td>0.004001</td>\n",
       "      <td>912</td>\n",
       "      <td>0.000211</td>\n",
       "      <td>1053</td>\n",
       "      <td>0.004093</td>\n",
       "      <td>572</td>\n",
       "      <td>0.001348</td>\n",
       "      <td>319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>C12865</td>\n",
       "      <td>2020-04-18T00:00:00Z</td>\n",
       "      <td>IMP323400</td>\n",
       "      <td>DEC8458</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY759</td>\n",
       "      <td>7318190000</td>\n",
       "      <td>43925</td>\n",
       "      <td>0.004510</td>\n",
       "      <td>877</td>\n",
       "      <td>0.000168</td>\n",
       "      <td>1078</td>\n",
       "      <td>0.002118</td>\n",
       "      <td>675</td>\n",
       "      <td>0.000683</td>\n",
       "      <td>328</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  SGD_NUM              SGD_DATE IMPORTER_TIN DECLARANT_CODE OFFICE_CODE  \\\n",
       "0  C12861  2020-04-18T00:00:00Z     IMPW2166        DEC6463    OFFICE92   \n",
       "1  C12862  2020-04-18T00:00:00Z     IMPW2166        DEC6463    OFFICE92   \n",
       "2  C12862  2020-04-18T00:00:00Z     IMPW2166        DEC6463    OFFICE92   \n",
       "3  C12865  2020-04-18T00:00:00Z    IMP323400        DEC8458    OFFICE92   \n",
       "4  C12865  2020-04-18T00:00:00Z    IMP323400        DEC8458    OFFICE92   \n",
       "\n",
       "  ORIGIN_CODE      HSCODE ITM_NUM       XGB  Ranking-XGB    XGB+LR  \\\n",
       "0    CNTRY277  2621900000   43831  0.007388          759  0.073774   \n",
       "1    CNTRY277  8205100000   43862  0.019617          367  0.120060   \n",
       "2    CNTRY277  8465990000   43863  0.003430          958  0.001457   \n",
       "3    CNTRY759  8484100000   43922  0.004001          912  0.000211   \n",
       "4    CNTRY759  7318190000   43925  0.004510          877  0.000168   \n",
       "\n",
       "   Ranking-XGB+LR  DATE_CLS  Ranking-DATE_CLS  DATE_REV  Ranking-DATE_REV  \n",
       "0             359  0.019338               357  0.006783               293  \n",
       "1             317  0.046201               280  0.021700               264  \n",
       "2             815  0.000113              1868 -0.012125              2047  \n",
       "3            1053  0.004093               572  0.001348               319  \n",
       "4            1078  0.002118               675  0.000683               328  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.03234546777627118, 0.08514176114145311, 0.06963891604093114)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(df3['XGB']), np.mean(df3['XGB+LR']), np.mean(df3['DATE_CLS'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "df3['INITIAL_ITM_CIF'] = df2['INITIAL_ITM_CIF']\n",
    "df3['INITIAL_ITM_TOTAL_TAX'] = df2['INITIAL_ITM_TOTAL_TAX']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Top-10 high fraudulent transactions selected by DATE_CLS:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SGD_NUM</th>\n",
       "      <th>ORIGIN_CODE</th>\n",
       "      <th>HSCODE</th>\n",
       "      <th>INITIAL_ITM_CIF</th>\n",
       "      <th>INITIAL_ITM_TOTAL_TAX</th>\n",
       "      <th>DATE_CLS</th>\n",
       "      <th>Ranking-DATE_CLS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>C13029</td>\n",
       "      <td>CNTRY759</td>\n",
       "      <td>3924100000</td>\n",
       "      <td>358600</td>\n",
       "      <td>0</td>\n",
       "      <td>0.999993</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1465</th>\n",
       "      <td>C45923</td>\n",
       "      <td>CNTRY278</td>\n",
       "      <td>8703311900</td>\n",
       "      <td>18050000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.999910</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>982</th>\n",
       "      <td>C45044</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>4008111000</td>\n",
       "      <td>7140991</td>\n",
       "      <td>1458167</td>\n",
       "      <td>0.999858</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>C44121</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>8708990000</td>\n",
       "      <td>96061113</td>\n",
       "      <td>0</td>\n",
       "      <td>0.999776</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>C13300</td>\n",
       "      <td>CNTRY825</td>\n",
       "      <td>1904100000</td>\n",
       "      <td>154577520</td>\n",
       "      <td>0</td>\n",
       "      <td>0.999726</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>C13309</td>\n",
       "      <td>CNTRY825</td>\n",
       "      <td>1904100000</td>\n",
       "      <td>154577520</td>\n",
       "      <td>0</td>\n",
       "      <td>0.999726</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1779</th>\n",
       "      <td>C46331</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>3209102000</td>\n",
       "      <td>6744814</td>\n",
       "      <td>0</td>\n",
       "      <td>0.999724</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>826</th>\n",
       "      <td>C44790</td>\n",
       "      <td>CNTRY759</td>\n",
       "      <td>3924909000</td>\n",
       "      <td>326</td>\n",
       "      <td>0</td>\n",
       "      <td>0.999651</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1763</th>\n",
       "      <td>C46304</td>\n",
       "      <td>CNTRY759</td>\n",
       "      <td>3924909000</td>\n",
       "      <td>361</td>\n",
       "      <td>0</td>\n",
       "      <td>0.999614</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>C13390</td>\n",
       "      <td>CNTRY277</td>\n",
       "      <td>8402120000</td>\n",
       "      <td>722000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.999598</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     SGD_NUM ORIGIN_CODE      HSCODE  INITIAL_ITM_CIF  INITIAL_ITM_TOTAL_TAX  \\\n",
       "71    C13029    CNTRY759  3924100000           358600                      0   \n",
       "1465  C45923    CNTRY278  8703311900         18050000                      0   \n",
       "982   C45044    CNTRY680  4008111000          7140991                1458167   \n",
       "437   C44121    CNTRY680  8708990000         96061113                      0   \n",
       "190   C13300    CNTRY825  1904100000        154577520                      0   \n",
       "195   C13309    CNTRY825  1904100000        154577520                      0   \n",
       "1779  C46331    CNTRY680  3209102000          6744814                      0   \n",
       "826   C44790    CNTRY759  3924909000              326                      0   \n",
       "1763  C46304    CNTRY759  3924909000              361                      0   \n",
       "213   C13390    CNTRY277  8402120000           722000                      0   \n",
       "\n",
       "      DATE_CLS  Ranking-DATE_CLS  \n",
       "71    0.999993                 1  \n",
       "1465  0.999910                 2  \n",
       "982   0.999858                 3  \n",
       "437   0.999776                 4  \n",
       "190   0.999726                 5  \n",
       "195   0.999726                 5  \n",
       "1779  0.999724                 7  \n",
       "826   0.999651                 8  \n",
       "1763  0.999614                 9  \n",
       "213   0.999598                10  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3[['SGD_NUM', 'ORIGIN_CODE', 'HSCODE','INITIAL_ITM_CIF', 'INITIAL_ITM_TOTAL_TAX', 'DATE_CLS', 'Ranking-DATE_CLS']].sort_values(by='DATE_CLS', ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bottom-10 low fraudulent transactions selected by DATE_CLS:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SGD_NUM</th>\n",
       "      <th>ORIGIN_CODE</th>\n",
       "      <th>HSCODE</th>\n",
       "      <th>INITIAL_ITM_CIF</th>\n",
       "      <th>INITIAL_ITM_TOTAL_TAX</th>\n",
       "      <th>DATE_REV</th>\n",
       "      <th>Ranking-DATE_REV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>C13535</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>1103110000</td>\n",
       "      <td>533654</td>\n",
       "      <td>35603</td>\n",
       "      <td>-0.018681</td>\n",
       "      <td>2115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1489</th>\n",
       "      <td>C45941</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>8436100000</td>\n",
       "      <td>16168951</td>\n",
       "      <td>1090989</td>\n",
       "      <td>-0.019718</td>\n",
       "      <td>2116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>C13027</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>1103110000</td>\n",
       "      <td>444345</td>\n",
       "      <td>29719</td>\n",
       "      <td>-0.019828</td>\n",
       "      <td>2117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>C13074</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>1103110000</td>\n",
       "      <td>444345</td>\n",
       "      <td>29719</td>\n",
       "      <td>-0.019828</td>\n",
       "      <td>2117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>C12911</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>1103110000</td>\n",
       "      <td>444345</td>\n",
       "      <td>29719</td>\n",
       "      <td>-0.019852</td>\n",
       "      <td>2119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>C13110</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>1103110000</td>\n",
       "      <td>444345</td>\n",
       "      <td>29719</td>\n",
       "      <td>-0.019876</td>\n",
       "      <td>2120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>951</th>\n",
       "      <td>C44997</td>\n",
       "      <td>CNTRY317</td>\n",
       "      <td>2906120000</td>\n",
       "      <td>965573</td>\n",
       "      <td>142226</td>\n",
       "      <td>-0.020896</td>\n",
       "      <td>2121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>C13123</td>\n",
       "      <td>CNTRY759</td>\n",
       "      <td>3402900000</td>\n",
       "      <td>13858903</td>\n",
       "      <td>4433535</td>\n",
       "      <td>-0.028144</td>\n",
       "      <td>2122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>C13124</td>\n",
       "      <td>CNTRY759</td>\n",
       "      <td>3402900000</td>\n",
       "      <td>25947912</td>\n",
       "      <td>8313922</td>\n",
       "      <td>-0.036790</td>\n",
       "      <td>2123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>C13397</td>\n",
       "      <td>CNTRY759</td>\n",
       "      <td>7615109000</td>\n",
       "      <td>399999</td>\n",
       "      <td>128470</td>\n",
       "      <td>-0.059058</td>\n",
       "      <td>2124</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     SGD_NUM ORIGIN_CODE      HSCODE  INITIAL_ITM_CIF  INITIAL_ITM_TOTAL_TAX  \\\n",
       "259   C13535    CNTRY680  1103110000           533654                  35603   \n",
       "1489  C45941    CNTRY680  8436100000         16168951                1090989   \n",
       "65    C13027    CNTRY680  1103110000           444345                  29719   \n",
       "77    C13074    CNTRY680  1103110000           444345                  29719   \n",
       "13    C12911    CNTRY680  1103110000           444345                  29719   \n",
       "86    C13110    CNTRY680  1103110000           444345                  29719   \n",
       "951   C44997    CNTRY317  2906120000           965573                 142226   \n",
       "96    C13123    CNTRY759  3402900000         13858903                4433535   \n",
       "97    C13124    CNTRY759  3402900000         25947912                8313922   \n",
       "218   C13397    CNTRY759  7615109000           399999                 128470   \n",
       "\n",
       "      DATE_REV  Ranking-DATE_REV  \n",
       "259  -0.018681              2115  \n",
       "1489 -0.019718              2116  \n",
       "65   -0.019828              2117  \n",
       "77   -0.019828              2117  \n",
       "13   -0.019852              2119  \n",
       "86   -0.019876              2120  \n",
       "951  -0.020896              2121  \n",
       "96   -0.028144              2122  \n",
       "97   -0.036790              2123  \n",
       "218  -0.059058              2124  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3[['SGD_NUM', 'ORIGIN_CODE', 'HSCODE','INITIAL_ITM_CIF', 'INITIAL_ITM_TOTAL_TAX', 'DATE_REV', 'Ranking-DATE_REV']].sort_values(by='DATE_REV', ascending=False).tail(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Top-10 high fraudulent transactions selected by DATE_REV. See that the prediction results of four different models are quite consistent. (Consider the total number of imports are over two thousands)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SGD_NUM</th>\n",
       "      <th>SGD_DATE</th>\n",
       "      <th>IMPORTER_TIN</th>\n",
       "      <th>DECLARANT_CODE</th>\n",
       "      <th>OFFICE_CODE</th>\n",
       "      <th>ORIGIN_CODE</th>\n",
       "      <th>HSCODE</th>\n",
       "      <th>ITM_NUM</th>\n",
       "      <th>XGB</th>\n",
       "      <th>Ranking-XGB</th>\n",
       "      <th>XGB+LR</th>\n",
       "      <th>Ranking-XGB+LR</th>\n",
       "      <th>DATE_CLS</th>\n",
       "      <th>Ranking-DATE_CLS</th>\n",
       "      <th>DATE_REV</th>\n",
       "      <th>Ranking-DATE_REV</th>\n",
       "      <th>INITIAL_ITM_CIF</th>\n",
       "      <th>INITIAL_ITM_TOTAL_TAX</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1465</th>\n",
       "      <td>C45923</td>\n",
       "      <td>2020-04-23T00:00:00Z</td>\n",
       "      <td>IMP878640</td>\n",
       "      <td>DEC1243</td>\n",
       "      <td>OFFICE51</td>\n",
       "      <td>CNTRY278</td>\n",
       "      <td>8703311900</td>\n",
       "      <td>43831</td>\n",
       "      <td>0.759778</td>\n",
       "      <td>5</td>\n",
       "      <td>0.994376</td>\n",
       "      <td>8</td>\n",
       "      <td>0.999910</td>\n",
       "      <td>2</td>\n",
       "      <td>0.844660</td>\n",
       "      <td>1</td>\n",
       "      <td>18050000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>C13271</td>\n",
       "      <td>2020-04-22T00:00:00Z</td>\n",
       "      <td>IMP167035</td>\n",
       "      <td>DECW2128</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY277</td>\n",
       "      <td>8537200000</td>\n",
       "      <td>43923</td>\n",
       "      <td>0.035469</td>\n",
       "      <td>250</td>\n",
       "      <td>0.164500</td>\n",
       "      <td>277</td>\n",
       "      <td>0.989521</td>\n",
       "      <td>33</td>\n",
       "      <td>0.816893</td>\n",
       "      <td>2</td>\n",
       "      <td>63315850</td>\n",
       "      <td>5735645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>C13390</td>\n",
       "      <td>2020-04-23T00:00:00Z</td>\n",
       "      <td>IMP167035</td>\n",
       "      <td>DECW2128</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY277</td>\n",
       "      <td>8402120000</td>\n",
       "      <td>43831</td>\n",
       "      <td>0.234485</td>\n",
       "      <td>93</td>\n",
       "      <td>0.426228</td>\n",
       "      <td>178</td>\n",
       "      <td>0.999598</td>\n",
       "      <td>10</td>\n",
       "      <td>0.803488</td>\n",
       "      <td>3</td>\n",
       "      <td>722000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>C13264</td>\n",
       "      <td>2020-04-22T00:00:00Z</td>\n",
       "      <td>IMP167035</td>\n",
       "      <td>DECW2128</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY277</td>\n",
       "      <td>8544600000</td>\n",
       "      <td>43831</td>\n",
       "      <td>0.082076</td>\n",
       "      <td>176</td>\n",
       "      <td>0.356276</td>\n",
       "      <td>196</td>\n",
       "      <td>0.993732</td>\n",
       "      <td>28</td>\n",
       "      <td>0.775895</td>\n",
       "      <td>4</td>\n",
       "      <td>47644256</td>\n",
       "      <td>4311400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>C13300</td>\n",
       "      <td>2020-04-22T00:00:00Z</td>\n",
       "      <td>IMPW843</td>\n",
       "      <td>DEC1451</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY825</td>\n",
       "      <td>1904100000</td>\n",
       "      <td>43831</td>\n",
       "      <td>0.224125</td>\n",
       "      <td>101</td>\n",
       "      <td>0.934511</td>\n",
       "      <td>58</td>\n",
       "      <td>0.999726</td>\n",
       "      <td>5</td>\n",
       "      <td>0.772243</td>\n",
       "      <td>5</td>\n",
       "      <td>154577520</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>C13309</td>\n",
       "      <td>2020-04-22T00:00:00Z</td>\n",
       "      <td>IMPW843</td>\n",
       "      <td>DEC1451</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY825</td>\n",
       "      <td>1904100000</td>\n",
       "      <td>43831</td>\n",
       "      <td>0.224125</td>\n",
       "      <td>101</td>\n",
       "      <td>0.934511</td>\n",
       "      <td>58</td>\n",
       "      <td>0.999726</td>\n",
       "      <td>5</td>\n",
       "      <td>0.772243</td>\n",
       "      <td>5</td>\n",
       "      <td>154577520</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>C13296</td>\n",
       "      <td>2020-04-22T00:00:00Z</td>\n",
       "      <td>IMP167035</td>\n",
       "      <td>DECW2128</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY277</td>\n",
       "      <td>8424890000</td>\n",
       "      <td>43831</td>\n",
       "      <td>0.200306</td>\n",
       "      <td>119</td>\n",
       "      <td>0.211856</td>\n",
       "      <td>247</td>\n",
       "      <td>0.998173</td>\n",
       "      <td>22</td>\n",
       "      <td>0.763678</td>\n",
       "      <td>7</td>\n",
       "      <td>652000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1779</th>\n",
       "      <td>C46331</td>\n",
       "      <td>2020-04-24T00:00:00Z</td>\n",
       "      <td>IMPW1174</td>\n",
       "      <td>DEC5307</td>\n",
       "      <td>OFFICE51</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>3209102000</td>\n",
       "      <td>43831</td>\n",
       "      <td>0.263730</td>\n",
       "      <td>81</td>\n",
       "      <td>0.971779</td>\n",
       "      <td>31</td>\n",
       "      <td>0.999724</td>\n",
       "      <td>7</td>\n",
       "      <td>0.759173</td>\n",
       "      <td>8</td>\n",
       "      <td>6744814</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1887</th>\n",
       "      <td>C46476</td>\n",
       "      <td>2020-04-24T00:00:00Z</td>\n",
       "      <td>IMP380660</td>\n",
       "      <td>DEC5307</td>\n",
       "      <td>OFFICE51</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>7312109900</td>\n",
       "      <td>43831</td>\n",
       "      <td>0.289004</td>\n",
       "      <td>71</td>\n",
       "      <td>0.953367</td>\n",
       "      <td>42</td>\n",
       "      <td>0.999562</td>\n",
       "      <td>12</td>\n",
       "      <td>0.756173</td>\n",
       "      <td>9</td>\n",
       "      <td>9331990</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458</th>\n",
       "      <td>C44162</td>\n",
       "      <td>2020-04-20T00:00:00Z</td>\n",
       "      <td>IMP938158</td>\n",
       "      <td>DEC1704</td>\n",
       "      <td>OFFICE51</td>\n",
       "      <td>CNTRY656</td>\n",
       "      <td>7202190000</td>\n",
       "      <td>44078</td>\n",
       "      <td>0.035285</td>\n",
       "      <td>251</td>\n",
       "      <td>0.657803</td>\n",
       "      <td>118</td>\n",
       "      <td>0.980941</td>\n",
       "      <td>38</td>\n",
       "      <td>0.737007</td>\n",
       "      <td>10</td>\n",
       "      <td>4826397</td>\n",
       "      <td>714074</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     SGD_NUM              SGD_DATE IMPORTER_TIN DECLARANT_CODE OFFICE_CODE  \\\n",
       "1465  C45923  2020-04-23T00:00:00Z    IMP878640        DEC1243    OFFICE51   \n",
       "151   C13271  2020-04-22T00:00:00Z    IMP167035       DECW2128    OFFICE92   \n",
       "213   C13390  2020-04-23T00:00:00Z    IMP167035       DECW2128    OFFICE92   \n",
       "144   C13264  2020-04-22T00:00:00Z    IMP167035       DECW2128    OFFICE92   \n",
       "190   C13300  2020-04-22T00:00:00Z      IMPW843        DEC1451    OFFICE92   \n",
       "195   C13309  2020-04-22T00:00:00Z      IMPW843        DEC1451    OFFICE92   \n",
       "187   C13296  2020-04-22T00:00:00Z    IMP167035       DECW2128    OFFICE92   \n",
       "1779  C46331  2020-04-24T00:00:00Z     IMPW1174        DEC5307    OFFICE51   \n",
       "1887  C46476  2020-04-24T00:00:00Z    IMP380660        DEC5307    OFFICE51   \n",
       "458   C44162  2020-04-20T00:00:00Z    IMP938158        DEC1704    OFFICE51   \n",
       "\n",
       "     ORIGIN_CODE      HSCODE ITM_NUM       XGB  Ranking-XGB    XGB+LR  \\\n",
       "1465    CNTRY278  8703311900   43831  0.759778            5  0.994376   \n",
       "151     CNTRY277  8537200000   43923  0.035469          250  0.164500   \n",
       "213     CNTRY277  8402120000   43831  0.234485           93  0.426228   \n",
       "144     CNTRY277  8544600000   43831  0.082076          176  0.356276   \n",
       "190     CNTRY825  1904100000   43831  0.224125          101  0.934511   \n",
       "195     CNTRY825  1904100000   43831  0.224125          101  0.934511   \n",
       "187     CNTRY277  8424890000   43831  0.200306          119  0.211856   \n",
       "1779    CNTRY680  3209102000   43831  0.263730           81  0.971779   \n",
       "1887    CNTRY680  7312109900   43831  0.289004           71  0.953367   \n",
       "458     CNTRY656  7202190000   44078  0.035285          251  0.657803   \n",
       "\n",
       "      Ranking-XGB+LR  DATE_CLS  Ranking-DATE_CLS  DATE_REV  Ranking-DATE_REV  \\\n",
       "1465               8  0.999910                 2  0.844660                 1   \n",
       "151              277  0.989521                33  0.816893                 2   \n",
       "213              178  0.999598                10  0.803488                 3   \n",
       "144              196  0.993732                28  0.775895                 4   \n",
       "190               58  0.999726                 5  0.772243                 5   \n",
       "195               58  0.999726                 5  0.772243                 5   \n",
       "187              247  0.998173                22  0.763678                 7   \n",
       "1779              31  0.999724                 7  0.759173                 8   \n",
       "1887              42  0.999562                12  0.756173                 9   \n",
       "458              118  0.980941                38  0.737007                10   \n",
       "\n",
       "      INITIAL_ITM_CIF  INITIAL_ITM_TOTAL_TAX  \n",
       "1465         18050000                      0  \n",
       "151          63315850                5735645  \n",
       "213            722000                      0  \n",
       "144          47644256                4311400  \n",
       "190         154577520                      0  \n",
       "195         154577520                      0  \n",
       "187            652000                      0  \n",
       "1779          6744814                      0  \n",
       "1887          9331990                      0  \n",
       "458           4826397                 714074  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3.sort_values(by='DATE_REV', ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bottom-10 low fraudulent transactions selected by DATE_REV. See that the prediction results of four different models are quite consistent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SGD_NUM</th>\n",
       "      <th>SGD_DATE</th>\n",
       "      <th>IMPORTER_TIN</th>\n",
       "      <th>DECLARANT_CODE</th>\n",
       "      <th>OFFICE_CODE</th>\n",
       "      <th>ORIGIN_CODE</th>\n",
       "      <th>HSCODE</th>\n",
       "      <th>ITM_NUM</th>\n",
       "      <th>XGB</th>\n",
       "      <th>Ranking-XGB</th>\n",
       "      <th>XGB+LR</th>\n",
       "      <th>Ranking-XGB+LR</th>\n",
       "      <th>DATE_CLS</th>\n",
       "      <th>Ranking-DATE_CLS</th>\n",
       "      <th>DATE_REV</th>\n",
       "      <th>Ranking-DATE_REV</th>\n",
       "      <th>INITIAL_ITM_CIF</th>\n",
       "      <th>INITIAL_ITM_TOTAL_TAX</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>C13369</td>\n",
       "      <td>2020-04-23T00:00:00Z</td>\n",
       "      <td>IMP256823</td>\n",
       "      <td>DEC7588</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY615</td>\n",
       "      <td>1105200000</td>\n",
       "      <td>43862</td>\n",
       "      <td>0.002127</td>\n",
       "      <td>1525</td>\n",
       "      <td>0.000151</td>\n",
       "      <td>1088</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>2115</td>\n",
       "      <td>-0.017046</td>\n",
       "      <td>2101</td>\n",
       "      <td>6492167</td>\n",
       "      <td>781274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>C13539</td>\n",
       "      <td>2020-04-24T00:00:00Z</td>\n",
       "      <td>IMP256823</td>\n",
       "      <td>DEC7588</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>1103110000</td>\n",
       "      <td>43862</td>\n",
       "      <td>0.003053</td>\n",
       "      <td>1056</td>\n",
       "      <td>0.002211</td>\n",
       "      <td>777</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>2116</td>\n",
       "      <td>-0.018646</td>\n",
       "      <td>2114</td>\n",
       "      <td>390337</td>\n",
       "      <td>26049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>C13427</td>\n",
       "      <td>2020-04-23T00:00:00Z</td>\n",
       "      <td>IMP256823</td>\n",
       "      <td>DEC7588</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY615</td>\n",
       "      <td>1105100000</td>\n",
       "      <td>43863</td>\n",
       "      <td>0.002355</td>\n",
       "      <td>1447</td>\n",
       "      <td>0.000310</td>\n",
       "      <td>1013</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>2117</td>\n",
       "      <td>-0.017673</td>\n",
       "      <td>2107</td>\n",
       "      <td>11229512</td>\n",
       "      <td>1349401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>C13369</td>\n",
       "      <td>2020-04-23T00:00:00Z</td>\n",
       "      <td>IMP256823</td>\n",
       "      <td>DEC7588</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY615</td>\n",
       "      <td>1105100000</td>\n",
       "      <td>43863</td>\n",
       "      <td>0.002355</td>\n",
       "      <td>1447</td>\n",
       "      <td>0.000310</td>\n",
       "      <td>1013</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>2117</td>\n",
       "      <td>-0.017673</td>\n",
       "      <td>2107</td>\n",
       "      <td>11945485</td>\n",
       "      <td>1437532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>265</th>\n",
       "      <td>C13539</td>\n",
       "      <td>2020-04-24T00:00:00Z</td>\n",
       "      <td>IMP256823</td>\n",
       "      <td>DEC7588</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>1105100000</td>\n",
       "      <td>43863</td>\n",
       "      <td>0.002219</td>\n",
       "      <td>1497</td>\n",
       "      <td>0.000189</td>\n",
       "      <td>1062</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>2119</td>\n",
       "      <td>-0.017876</td>\n",
       "      <td>2110</td>\n",
       "      <td>3954454</td>\n",
       "      <td>475464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>C12911</td>\n",
       "      <td>2020-04-20T00:00:00Z</td>\n",
       "      <td>IMP256823</td>\n",
       "      <td>DEC7588</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>1105100000</td>\n",
       "      <td>43863</td>\n",
       "      <td>0.002662</td>\n",
       "      <td>1186</td>\n",
       "      <td>0.000051</td>\n",
       "      <td>1135</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>2120</td>\n",
       "      <td>-0.018079</td>\n",
       "      <td>2111</td>\n",
       "      <td>8133572</td>\n",
       "      <td>979096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>C13110</td>\n",
       "      <td>2020-04-21T00:00:00Z</td>\n",
       "      <td>IMP256823</td>\n",
       "      <td>DEC7588</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>1103110000</td>\n",
       "      <td>43862</td>\n",
       "      <td>0.002898</td>\n",
       "      <td>1105</td>\n",
       "      <td>0.000573</td>\n",
       "      <td>932</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>2121</td>\n",
       "      <td>-0.019876</td>\n",
       "      <td>2120</td>\n",
       "      <td>444345</td>\n",
       "      <td>29719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>C12911</td>\n",
       "      <td>2020-04-20T00:00:00Z</td>\n",
       "      <td>IMP256823</td>\n",
       "      <td>DEC7588</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>1103110000</td>\n",
       "      <td>43862</td>\n",
       "      <td>0.002500</td>\n",
       "      <td>1218</td>\n",
       "      <td>0.000313</td>\n",
       "      <td>1011</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>2122</td>\n",
       "      <td>-0.019852</td>\n",
       "      <td>2119</td>\n",
       "      <td>444345</td>\n",
       "      <td>29719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>C13027</td>\n",
       "      <td>2020-04-21T00:00:00Z</td>\n",
       "      <td>IMP256823</td>\n",
       "      <td>DEC7588</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>1103110000</td>\n",
       "      <td>43862</td>\n",
       "      <td>0.002554</td>\n",
       "      <td>1205</td>\n",
       "      <td>0.000453</td>\n",
       "      <td>968</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>2123</td>\n",
       "      <td>-0.019828</td>\n",
       "      <td>2117</td>\n",
       "      <td>444345</td>\n",
       "      <td>29719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>C13074</td>\n",
       "      <td>2020-04-21T00:00:00Z</td>\n",
       "      <td>IMP256823</td>\n",
       "      <td>DEC7588</td>\n",
       "      <td>OFFICE92</td>\n",
       "      <td>CNTRY680</td>\n",
       "      <td>1103110000</td>\n",
       "      <td>43862</td>\n",
       "      <td>0.002554</td>\n",
       "      <td>1205</td>\n",
       "      <td>0.000453</td>\n",
       "      <td>968</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>2123</td>\n",
       "      <td>-0.019828</td>\n",
       "      <td>2117</td>\n",
       "      <td>444345</td>\n",
       "      <td>29719</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "    SGD_NUM              SGD_DATE IMPORTER_TIN DECLARANT_CODE OFFICE_CODE  \\\n",
       "208  C13369  2020-04-23T00:00:00Z    IMP256823        DEC7588    OFFICE92   \n",
       "264  C13539  2020-04-24T00:00:00Z    IMP256823        DEC7588    OFFICE92   \n",
       "231  C13427  2020-04-23T00:00:00Z    IMP256823        DEC7588    OFFICE92   \n",
       "209  C13369  2020-04-23T00:00:00Z    IMP256823        DEC7588    OFFICE92   \n",
       "265  C13539  2020-04-24T00:00:00Z    IMP256823        DEC7588    OFFICE92   \n",
       "14   C12911  2020-04-20T00:00:00Z    IMP256823        DEC7588    OFFICE92   \n",
       "86   C13110  2020-04-21T00:00:00Z    IMP256823        DEC7588    OFFICE92   \n",
       "13   C12911  2020-04-20T00:00:00Z    IMP256823        DEC7588    OFFICE92   \n",
       "65   C13027  2020-04-21T00:00:00Z    IMP256823        DEC7588    OFFICE92   \n",
       "77   C13074  2020-04-21T00:00:00Z    IMP256823        DEC7588    OFFICE92   \n",
       "\n",
       "    ORIGIN_CODE      HSCODE ITM_NUM       XGB  Ranking-XGB    XGB+LR  \\\n",
       "208    CNTRY615  1105200000   43862  0.002127         1525  0.000151   \n",
       "264    CNTRY680  1103110000   43862  0.003053         1056  0.002211   \n",
       "231    CNTRY615  1105100000   43863  0.002355         1447  0.000310   \n",
       "209    CNTRY615  1105100000   43863  0.002355         1447  0.000310   \n",
       "265    CNTRY680  1105100000   43863  0.002219         1497  0.000189   \n",
       "14     CNTRY680  1105100000   43863  0.002662         1186  0.000051   \n",
       "86     CNTRY680  1103110000   43862  0.002898         1105  0.000573   \n",
       "13     CNTRY680  1103110000   43862  0.002500         1218  0.000313   \n",
       "65     CNTRY680  1103110000   43862  0.002554         1205  0.000453   \n",
       "77     CNTRY680  1103110000   43862  0.002554         1205  0.000453   \n",
       "\n",
       "     Ranking-XGB+LR  DATE_CLS  Ranking-DATE_CLS  DATE_REV  Ranking-DATE_REV  \\\n",
       "208            1088  0.000002              2115 -0.017046              2101   \n",
       "264             777  0.000002              2116 -0.018646              2114   \n",
       "231            1013  0.000002              2117 -0.017673              2107   \n",
       "209            1013  0.000002              2117 -0.017673              2107   \n",
       "265            1062  0.000002              2119 -0.017876              2110   \n",
       "14             1135  0.000001              2120 -0.018079              2111   \n",
       "86              932  0.000001              2121 -0.019876              2120   \n",
       "13             1011  0.000001              2122 -0.019852              2119   \n",
       "65              968  0.000001              2123 -0.019828              2117   \n",
       "77              968  0.000001              2123 -0.019828              2117   \n",
       "\n",
       "     INITIAL_ITM_CIF  INITIAL_ITM_TOTAL_TAX  \n",
       "208          6492167                 781274  \n",
       "264           390337                  26049  \n",
       "231         11229512                1349401  \n",
       "209         11945485                1437532  \n",
       "265          3954454                 475464  \n",
       "14           8133572                 979096  \n",
       "86            444345                  29719  \n",
       "13            444345                  29719  \n",
       "65            444345                  29719  \n",
       "77            444345                  29719  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3.sort_values(by='DATE_CLS', ascending=False).tail(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Further Interpretation of DATE_REV \n",
    "The DATE model optimizes both fraud probability and expected revenue, denoted as y_cls and y_rev, respectively (DATE_CLS, DATE_REV in the result file). However, in the course of minimizing MSE for revenue regression, we use normalization techniques to prevent the effect of the outlier. Also, the regression is done very conservatively due to the highly imbalanced nature, e.g., 'revenue' (=RAISED_AMOUNT_TAX) of the most training cases are 0. So, it is difficult to retrieve the expected revenue with an actual scale. Therefore, DATE_REV should not be interpreted directly as expected revenue. But, their relative order -- ranking, is very reliable, that's why the seized revenue of 1% selectivity ratio was almost 50%. For the live test, we highly recommend setting up relative thresholds, e.g., nth percentile, by referring to these weekly pilot test results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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