aggregation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from os import listdir\n",
    "from os.path import isfile,abspath, join,curdir\n",
    "import sys\n",
    "sys.path.insert(0, './common/')\n",
    "import aggregation\n",
    "import csv_utils\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['/home/zenbook/Work/github/quora_npl/data/submissions_for_aggregation/submission_1008PM-December-12-2018.csv',\n",
       " '/home/zenbook/Work/github/quora_npl/data/submissions_for_aggregation/submission_0449PM-December-11-2018.csv',\n",
       " '/home/zenbook/Work/github/quora_npl/data/submissions_for_aggregation/submission_0823AM-December-12-2018.csv',\n",
       " '/home/zenbook/Work/github/quora_npl/data/submissions_for_aggregation/submission_0135PM-December-09-2018.csv',\n",
       " '/home/zenbook/Work/github/quora_npl/data/submissions_for_aggregation/submission_1114PM-December-08-2018.csv',\n",
       " '/home/zenbook/Work/github/quora_npl/data/submissions_for_aggregation/submission_0303PM-December-09-2018.csv',\n",
       " '/home/zenbook/Work/github/quora_npl/data/submissions_for_aggregation/submission_0115PM-December-11-2018.csv']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FOLDER = os.path.join('data', 'submissions_for_aggregation')\n",
    "CURRENT_PATH = abspath(curdir)\n",
    "FULL_PATH = join(CURRENT_PATH, FOLDER)\n",
    "onlyfiles = [join(FULL_PATH, f) for f in listdir(FOLDER) if isfile(join(FULL_PATH, f))]\n",
    "onlyfiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>test_id</th>\n",
       "      <th>col0</th>\n",
       "      <th>col1</th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "      <th>col4</th>\n",
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       "      <th>0</th>\n",
       "      <td>15</td>\n",
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       "      <th>1</th>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>34</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>46</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>51</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>58</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <th>11</th>\n",
       "      <td>72</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>73</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>78</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>81</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>88</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>94</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>107</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>113</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    test_id  col0  col1  col2  col3  col4  col5  col6\n",
       "0        15     1     1     1     1     1     1     0\n",
       "1        20     0     0     0     0     1     0     0\n",
       "2        21     1     0     1     0     0     0     0\n",
       "3        23     0     0     0     0     0     0     0\n",
       "4        34     1     0     0     0     0     0     0\n",
       "5        46     0     0     0     0     0     0     0\n",
       "6        48     1     1     1     1     0     0     1\n",
       "7        51     1     0     1     0     0     1     0\n",
       "8        54     0     0     0     0     0     0     0\n",
       "9        56     0     0     0     0     0     0     0\n",
       "10       58     1     1     1     1     1     1     1\n",
       "11       72     1     1     1     1     1     1     1\n",
       "12       73     1     1     1     1     1     1     1\n",
       "13       78     0     1     0     1     1     0     0\n",
       "14       81     0     0     0     0     0     0     0\n",
       "15       88     1     1     1     1     1     1     1\n",
       "16       94     0     0     0     0     0     0     0\n",
       "17      100     1     1     1     1     1     1     1\n",
       "18      107     1     0     1     0     0     0     0\n",
       "19      113     1     1     1     1     1     0     1"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(onlyfiles[0])\n",
    "\n",
    "files = onlyfiles[1:]\n",
    "i = 1\n",
    "for p in files:\n",
    "    df = pd.merge(df, pd.read_csv(p), on='test_id', how='inner')\n",
    "    i += 1\n",
    "df.columns = ['test_id'] + ['col'+str(j) for j in range(i)]\n",
    "    \n",
    "df.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "aggregate = aggregation.aggregateXavi\n",
    "#aggregate = aggregation.aggregateAlbert\n",
    "\n",
    "# Mean aggregation\n",
    "# weights to each model (giving the same weight to all models)\n",
    "scores = np.ones(7) # because there are 7 models\n",
    "aggregated = aggregate(df, scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>test_id</th>\n",
       "      <th>winner</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
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      "text/plain": [
       "   test_id  winner\n",
       "0       15       1\n",
       "1       20       0\n",
       "2       21       0\n",
       "3       23       0\n",
       "4       34       0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aggregated.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "saved in:  /home/zenbook/Work/github/quora_npl/data/submissions/submission_0920PM-December-13-2018.csv\n"
     ]
    }
   ],
   "source": [
    "csv_utils.create_csvs(aggregated['winner'], aggregated['test_id'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Score Kaggle: 0.85918"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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