Dota2SkillPrediction_Tutorial.ipynb

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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Определение опытных игроков Dota 2 (руководство по решению)\n",
    "\n",
    "В игре Dota 2 участвуют две стороны: команды сил Света (The Radiant) и сил Тьмы (The Dire). Каждая команда состоит из 5 игроков — персонажей со своими уникальными способностями. Перед началом матча каждый игрок выбирает себе одного героя из 116 возможных. Цель игры — разрушить трон, находящийся на базе противника.\n",
    "\n",
    "Повышая игровые навыки, игроки повышают свой рейтинг и получают медали опыта. Эксперты по игре Dota 2 утверждают, что легко могут отличить матч новичка от игры опытного игрока.\n",
    "\n",
    "**Задача — построить алгоритм, который сможет определять опытность игрока по статистике из одного матча.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Таблицы с данными\n",
    "\n",
    "Рассмотрим упрощённый набор данных в виде таблиц `skill_train.csv` и `skill_test.csv`, с которыми удобно оперировать и подавать в алгоритмы машинного обучения."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:37.801449Z",
     "start_time": "2019-03-08T17:10:37.099793Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline\n",
    "import pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:39.259722Z",
     "start_time": "2019-03-08T17:10:37.804809Z"
    }
   },
   "outputs": [],
   "source": [
    "df_train = pandas.read_csv('data/dota2_skill_train.csv', index_col='id')\n",
    "df_test = pandas.read_csv('data/dota2_skill_test.csv', index_col='id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:39.298743Z",
     "start_time": "2019-03-08T17:10:39.263048Z"
    }
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>skilled</th>\n",
       "      <th>player_team</th>\n",
       "      <th>winner_team</th>\n",
       "      <th>duration</th>\n",
       "      <th>pre_game_duration</th>\n",
       "      <th>first_blood_time</th>\n",
       "      <th>first_blood_claimed</th>\n",
       "      <th>hero_id</th>\n",
       "      <th>hero_pick_order</th>\n",
       "      <th>leaver_status</th>\n",
       "      <th>...</th>\n",
       "      <th>avg_deaths_x16</th>\n",
       "      <th>avg_assists_x16</th>\n",
       "      <th>avg_gpm_x16</th>\n",
       "      <th>avg_xpm_x16</th>\n",
       "      <th>best_kills_x16</th>\n",
       "      <th>best_assists_x16</th>\n",
       "      <th>best_gpm_x16</th>\n",
       "      <th>best_xpm_x16</th>\n",
       "      <th>win_streak</th>\n",
       "      <th>best_win_streak</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>dire</td>\n",
       "      <td>dire</td>\n",
       "      <td>2140</td>\n",
       "      <td>90</td>\n",
       "      <td>129</td>\n",
       "      <td>0</td>\n",
       "      <td>90</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>15</td>\n",
       "      <td>352</td>\n",
       "      <td>430</td>\n",
       "      <td>10</td>\n",
       "      <td>30</td>\n",
       "      <td>551</td>\n",
       "      <td>745</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>radiant</td>\n",
       "      <td>radiant</td>\n",
       "      <td>2138</td>\n",
       "      <td>90</td>\n",
       "      <td>174</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>19</td>\n",
       "      <td>294</td>\n",
       "      <td>425</td>\n",
       "      <td>13</td>\n",
       "      <td>37</td>\n",
       "      <td>445</td>\n",
       "      <td>717</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0</td>\n",
       "      <td>radiant</td>\n",
       "      <td>radiant</td>\n",
       "      <td>3547</td>\n",
       "      <td>90</td>\n",
       "      <td>360</td>\n",
       "      <td>0</td>\n",
       "      <td>81</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>493</td>\n",
       "      <td>543</td>\n",
       "      <td>23</td>\n",
       "      <td>18</td>\n",
       "      <td>691</td>\n",
       "      <td>762</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1</td>\n",
       "      <td>dire</td>\n",
       "      <td>radiant</td>\n",
       "      <td>1878</td>\n",
       "      <td>90</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>74</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
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       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>515</td>\n",
       "      <td>583</td>\n",
       "      <td>25</td>\n",
       "      <td>34</td>\n",
       "      <td>869</td>\n",
       "      <td>935</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1</td>\n",
       "      <td>dire</td>\n",
       "      <td>radiant</td>\n",
       "      <td>2232</td>\n",
       "      <td>90</td>\n",
       "      <td>129</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
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       "      <td>16</td>\n",
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       "      <td>797</td>\n",
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       "      <td>9</td>\n",
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       "<p>5 rows × 57 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    skilled player_team winner_team  duration  pre_game_duration  \\\n",
       "id                                                                 \n",
       "7         1        dire        dire      2140                 90   \n",
       "8         0     radiant     radiant      2138                 90   \n",
       "12        0     radiant     radiant      3547                 90   \n",
       "13        1        dire     radiant      1878                 90   \n",
       "14        1        dire     radiant      2232                 90   \n",
       "\n",
       "    first_blood_time  first_blood_claimed  hero_id  hero_pick_order  \\\n",
       "id                                                                    \n",
       "7                129                    0       90                9   \n",
       "8                174                    0        5                5   \n",
       "12               360                    0       81                7   \n",
       "13                28                    0       74                9   \n",
       "14               129                    0       14                6   \n",
       "\n",
       "    leaver_status       ...         avg_deaths_x16  avg_assists_x16  \\\n",
       "id                      ...                                           \n",
       "7               0       ...                      8               15   \n",
       "8               0       ...                      9               19   \n",
       "12              0       ...                      7                9   \n",
       "13              0       ...                      7               12   \n",
       "14              0       ...                     10               16   \n",
       "\n",
       "    avg_gpm_x16  avg_xpm_x16  best_kills_x16  best_assists_x16  best_gpm_x16  \\\n",
       "id                                                                             \n",
       "7           352          430              10                30           551   \n",
       "8           294          425              13                37           445   \n",
       "12          493          543              23                18           691   \n",
       "13          515          583              25                34           869   \n",
       "14          337          452              34                43           672   \n",
       "\n",
       "    best_xpm_x16  win_streak  best_win_streak  \n",
       "id                                             \n",
       "7            745           2                5  \n",
       "8            717           2               12  \n",
       "12           762           3                3  \n",
       "13           935           0                6  \n",
       "14           797           0                9  \n",
       "\n",
       "[5 rows x 57 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Значение полей таблиц с данными\n",
    "\n",
    "Целевая переменная:\n",
    "- `skilled`: 1 — опытный игрок, 0 — новичок; эту колонку необходимо предсказывать для тестовой выборки\n",
    "\n",
    "Информация про матч:\n",
    "- `player_team`: команда, за которую играл игрок (`radiant` или `dire`)\n",
    "- `winner_team`: победившая команда\n",
    "- `hero_id`: идентификатор героя, за которого играл целевой игрок (расшифровку см. в таблице `heroes.csv`)\n",
    "- `duration`: длительность игры в секундах\n",
    "- `first_blood_time`: время события \"первая кровь\"\n",
    "- `first_blood_claimed`: сделал ли целевой игрок \"первую кровь\"\n",
    "- `party_players`: сколько игроков было в \"пати\" вместе с целевым\n",
    "\n",
    "Показатели целевого игрока в матче:\n",
    "- `kills`, `deaths`, `assists`, `denies`, `last_hits` — основные игровые показатели (число убийств вражеских героев, число смертей, и др.)\n",
    "- `stuns`: нанесенные \"оглушения\" (в секундах)\n",
    "- `level`: уровень, которого достиг герой к концу игры\n",
    "- `net_worth`: общая стоимость всего инвентаря героя\n",
    "- `gold`: число золота на момент игры\n",
    "- `gold_spent`: сумма потраченного золота за всю игру\n",
    "- `gold_per_min`: скорость зарабатывания золота\n",
    "- `xp_per_min`: скорость получения опыта\n",
    "- `hero_damage`: суммарный урон по вражеским героям\n",
    "- `tower_damage`: сумарный урон по вражеским башням\n",
    "- `hero_healing`: суммарное восстановленное здоровье союзных героев \n",
    "- `team_fight_participation`: участие в драках\n",
    "- `observer_wards_placed`, `sentry_wards_placed`: количество установленных на карту \"вардов\" (предметы, дающие обзор)\n",
    "- `rune_pickups`: количество собранных рун\n",
    "- `radiant_tower_status`, `dire_tower_status`: состояние башен команд на конец игры (см. [расшифровку](https://wiki.teamfortress.com/wiki/WebAPI/GetMatchDetails#Tower_Status))\n",
    "- `radiant_barracks_status`, `dire_barracks_status`: состояние бараков команд на конец игры (см. [расшифровку](https://wiki.teamfortress.com/wiki/WebAPI/GetMatchDetails#Barracks_Status))\n",
    "\n",
    "Показатели по последним матчам игрока:\n",
    "- `avg_kills_x16`, `avg_deaths_x16`, `avg_assists_x16`, `avg_gpm_x16`, `avg_xpm_x16`: средние значения показателей за последние 16 игр\n",
    "- `best_kills_x16`, `best_assists_x16`, `best_gpm_x16`, `best_xpm_x16`: максимальные значения показателей за последние 16 игр\n",
    "- `win_streak`, `best_win_streak`: число подряд выигранных матчей до текущего, максимальное число подряд выигранных матчей"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Расширенный набор данных\n",
    "\n",
    "В дополнение к таблицам имеются расширенные наборы данных: `skill_train.jsonlines`, `skill_test.jsonlines` — это текстовые файлы, в каждой строчке записан объект в формате [JSON](https://ru.wikipedia.org/wiki/JSON). В объектах есть все поля из таблиц, но кроме этого есть дополнительные поля, список приведен ниже."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Пример чтения файла в формате \"JSON Lines\":"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:39.311517Z",
     "start_time": "2019-03-08T17:10:39.303490Z"
    }
   },
   "outputs": [],
   "source": [
    "with open('data/dota2_skill_train.jsonlines') as fin:\n",
    "    for line in fin:\n",
    "        record = json.loads(line)\n",
    "        # обработка record\n",
    "        \n",
    "        break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Значения полей\n",
    "\n",
    "- `damage_targets`: количество нанесенного игроком урона по всем видам юнитов\n",
    "- `radiant_heroes`, `dire_heroes`: список идентификаторов героев у всех игроков в команде (расшифровку см. в таблице `heroes.csv`)\n",
    "- `final_items`: предметы инвентаря, собранные игроком к концу игры (0 означает отсутствие предмета в соответствующем слоте, расшифровку предметов см. в таблице `items.csv`)\n",
    "- `level_up_times`: время, в которое герой игрока повышал уровень\n",
    "- `ability_upgrades`: последовательность улучшений умений, которые делал игрок (возможность улучшить умение возникает при повышении уровня героя, расшифровка умений см. в таблице `abilities.csv`)\n",
    "- `item_purchase_log`\n",
    "- `series`: временные ряды изменения игровых показателей во времени\n",
    "  - `time`: отсчеты времени\n",
    "  - `radiant_gold`, `dire_gold`: суммарное число золота, заработанного командами\n",
    "  - `player_gold`: число золота, заработанное игроком"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Рассмотрим один пример из расширенного набора. Как и в таблицах, каждая запись имеет свой идентификатор:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
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     "end_time": "2019-03-08T17:10:39.325009Z",
     "start_time": "2019-03-08T17:10:39.315303Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "record['id']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Изменение золота в игре"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:39.575686Z",
     "start_time": "2019-03-08T17:10:39.328745Z"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1104bc4a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "series = record['series']\n",
    "plot(series['time'], series['radiant_gold'])\n",
    "plot(series['time'], series['dire_gold'])\n",
    "plot(series['time'], series['player_gold'])\n",
    "title('Gold time series')\n",
    "_ = legend(['radiant', 'dire', 'player'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "В качестве вспомогательной информации есть описание героев `heroes.csv`, предметов `items.csv` и умений `abilities.csv`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Составы команд"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:39.644937Z",
     "start_time": "2019-03-08T17:10:39.580393Z"
    }
   },
   "outputs": [],
   "source": [
    "df_heroes = pandas.read_csv('data/dota2_heroes.csv', index_col='hero_id')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Герои команды **Radiant**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:39.728148Z",
     "start_time": "2019-03-08T17:10:39.649452Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>name</th>\n",
       "      <th>localized_name</th>\n",
       "      <th>roles</th>\n",
       "      <th>agi_gain</th>\n",
       "      <th>attack_range</th>\n",
       "      <th>attack_rate</th>\n",
       "      <th>attack_type</th>\n",
       "      <th>base_agi</th>\n",
       "      <th>base_armor</th>\n",
       "      <th>base_attack_max</th>\n",
       "      <th>...</th>\n",
       "      <th>base_mr</th>\n",
       "      <th>base_str</th>\n",
       "      <th>cm_enabled</th>\n",
       "      <th>int_gain</th>\n",
       "      <th>legs</th>\n",
       "      <th>move_speed</th>\n",
       "      <th>primary_attr</th>\n",
       "      <th>projectile_speed</th>\n",
       "      <th>str_gain</th>\n",
       "      <th>turn_rate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hero_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>npc_dota_hero_pangolier</td>\n",
       "      <td>Pangolier</td>\n",
       "      <td>['Carry', 'Nuker', 'Disabler', 'Durable', 'Esc...</td>\n",
       "      <td>3.2</td>\n",
       "      <td>150</td>\n",
       "      <td>1.7</td>\n",
       "      <td>Melee</td>\n",
       "      <td>18</td>\n",
       "      <td>1.0</td>\n",
       "      <td>39</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>17</td>\n",
       "      <td>True</td>\n",
       "      <td>1.9</td>\n",
       "      <td>2</td>\n",
       "      <td>305</td>\n",
       "      <td>agi</td>\n",
       "      <td>900</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>npc_dota_hero_earthshaker</td>\n",
       "      <td>Earthshaker</td>\n",
       "      <td>['Support', 'Initiator', 'Disabler', 'Nuker']</td>\n",
       "      <td>1.4</td>\n",
       "      <td>150</td>\n",
       "      <td>1.7</td>\n",
       "      <td>Melee</td>\n",
       "      <td>12</td>\n",
       "      <td>0.0</td>\n",
       "      <td>37</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>True</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2</td>\n",
       "      <td>310</td>\n",
       "      <td>str</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>0.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>npc_dota_hero_skywrath_mage</td>\n",
       "      <td>Skywrath Mage</td>\n",
       "      <td>['Support', 'Nuker', 'Disabler']</td>\n",
       "      <td>0.8</td>\n",
       "      <td>600</td>\n",
       "      <td>1.7</td>\n",
       "      <td>Ranged</td>\n",
       "      <td>13</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>24</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>21</td>\n",
       "      <td>True</td>\n",
       "      <td>4.1</td>\n",
       "      <td>2</td>\n",
       "      <td>325</td>\n",
       "      <td>int</td>\n",
       "      <td>1000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>npc_dota_hero_oracle</td>\n",
       "      <td>Oracle</td>\n",
       "      <td>['Support', 'Nuker', 'Disabler', 'Escape']</td>\n",
       "      <td>1.7</td>\n",
       "      <td>620</td>\n",
       "      <td>1.4</td>\n",
       "      <td>Ranged</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>True</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2</td>\n",
       "      <td>300</td>\n",
       "      <td>int</td>\n",
       "      <td>900</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>npc_dota_hero_chaos_knight</td>\n",
       "      <td>Chaos Knight</td>\n",
       "      <td>['Carry', 'Disabler', 'Durable', 'Pusher', 'In...</td>\n",
       "      <td>2.1</td>\n",
       "      <td>150</td>\n",
       "      <td>1.7</td>\n",
       "      <td>Melee</td>\n",
       "      <td>14</td>\n",
       "      <td>1.0</td>\n",
       "      <td>59</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>True</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2</td>\n",
       "      <td>320</td>\n",
       "      <td>str</td>\n",
       "      <td>900</td>\n",
       "      <td>3.7</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                name localized_name  \\\n",
       "hero_id                                               \n",
       "120          npc_dota_hero_pangolier      Pangolier   \n",
       "7          npc_dota_hero_earthshaker    Earthshaker   \n",
       "101      npc_dota_hero_skywrath_mage  Skywrath Mage   \n",
       "111             npc_dota_hero_oracle         Oracle   \n",
       "81        npc_dota_hero_chaos_knight   Chaos Knight   \n",
       "\n",
       "                                                     roles  agi_gain  \\\n",
       "hero_id                                                                \n",
       "120      ['Carry', 'Nuker', 'Disabler', 'Durable', 'Esc...       3.2   \n",
       "7            ['Support', 'Initiator', 'Disabler', 'Nuker']       1.4   \n",
       "101                       ['Support', 'Nuker', 'Disabler']       0.8   \n",
       "111             ['Support', 'Nuker', 'Disabler', 'Escape']       1.7   \n",
       "81       ['Carry', 'Disabler', 'Durable', 'Pusher', 'In...       2.1   \n",
       "\n",
       "         attack_range  attack_rate attack_type  base_agi  base_armor  \\\n",
       "hero_id                                                                \n",
       "120               150          1.7       Melee        18         1.0   \n",
       "7                 150          1.7       Melee        12         0.0   \n",
       "101               600          1.7      Ranged        13        -2.0   \n",
       "111               620          1.4      Ranged        15         0.0   \n",
       "81                150          1.7       Melee        14         1.0   \n",
       "\n",
       "         base_attack_max    ...      base_mr  base_str  cm_enabled  int_gain  \\\n",
       "hero_id                     ...                                                \n",
       "120                   39    ...           25        17        True       1.9   \n",
       "7                     37    ...           25        22        True       1.8   \n",
       "101                   24    ...           25        21        True       4.1   \n",
       "111                   24    ...           25        20        True       4.0   \n",
       "81                    59    ...           25        22        True       1.2   \n",
       "\n",
       "         legs  move_speed  primary_attr  projectile_speed  str_gain  turn_rate  \n",
       "hero_id                                                                         \n",
       "120         2         305           agi               900       2.5        1.0  \n",
       "7           2         310           str                 0       3.7        0.9  \n",
       "101         2         325           int              1000       2.0        0.5  \n",
       "111         2         300           int               900       2.4        0.7  \n",
       "81          2         320           str               900       3.7        0.5  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_heroes.loc[record['radiant_heroes'], :]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Герои команды **Dire**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:39.774607Z",
     "start_time": "2019-03-08T17:10:39.732172Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
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       "    .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>name</th>\n",
       "      <th>localized_name</th>\n",
       "      <th>roles</th>\n",
       "      <th>agi_gain</th>\n",
       "      <th>attack_range</th>\n",
       "      <th>attack_rate</th>\n",
       "      <th>attack_type</th>\n",
       "      <th>base_agi</th>\n",
       "      <th>base_armor</th>\n",
       "      <th>base_attack_max</th>\n",
       "      <th>...</th>\n",
       "      <th>base_mr</th>\n",
       "      <th>base_str</th>\n",
       "      <th>cm_enabled</th>\n",
       "      <th>int_gain</th>\n",
       "      <th>legs</th>\n",
       "      <th>move_speed</th>\n",
       "      <th>primary_attr</th>\n",
       "      <th>projectile_speed</th>\n",
       "      <th>str_gain</th>\n",
       "      <th>turn_rate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hero_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>npc_dota_hero_pugna</td>\n",
       "      <td>Pugna</td>\n",
       "      <td>['Nuker', 'Pusher']</td>\n",
       "      <td>1.0</td>\n",
       "      <td>630</td>\n",
       "      <td>1.7</td>\n",
       "      <td>Ranged</td>\n",
       "      <td>16</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>19</td>\n",
       "      <td>True</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2</td>\n",
       "      <td>330</td>\n",
       "      <td>int</td>\n",
       "      <td>900</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>npc_dota_hero_bounty_hunter</td>\n",
       "      <td>Bounty Hunter</td>\n",
       "      <td>['Escape', 'Nuker']</td>\n",
       "      <td>2.6</td>\n",
       "      <td>150</td>\n",
       "      <td>1.7</td>\n",
       "      <td>Melee</td>\n",
       "      <td>21</td>\n",
       "      <td>3.0</td>\n",
       "      <td>38</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>True</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>315</td>\n",
       "      <td>agi</td>\n",
       "      <td>900</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>npc_dota_hero_keeper_of_the_light</td>\n",
       "      <td>Keeper of the Light</td>\n",
       "      <td>['Support', 'Nuker', 'Disabler', 'Jungler']</td>\n",
       "      <td>1.6</td>\n",
       "      <td>600</td>\n",
       "      <td>1.7</td>\n",
       "      <td>Ranged</td>\n",
       "      <td>15</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>27</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>16</td>\n",
       "      <td>True</td>\n",
       "      <td>3.2</td>\n",
       "      <td>2</td>\n",
       "      <td>330</td>\n",
       "      <td>int</td>\n",
       "      <td>900</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>npc_dota_hero_mars</td>\n",
       "      <td>Mars</td>\n",
       "      <td>['Carry', 'Initiator', 'Disabler', 'Durable']</td>\n",
       "      <td>1.9</td>\n",
       "      <td>250</td>\n",
       "      <td>1.8</td>\n",
       "      <td>Melee</td>\n",
       "      <td>20</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>False</td>\n",
       "      <td>1.4</td>\n",
       "      <td>2</td>\n",
       "      <td>310</td>\n",
       "      <td>str</td>\n",
       "      <td>900</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>npc_dota_hero_furion</td>\n",
       "      <td>Nature's Prophet</td>\n",
       "      <td>['Carry', 'Jungler', 'Pusher', 'Escape', 'Nuker']</td>\n",
       "      <td>3.3</td>\n",
       "      <td>600</td>\n",
       "      <td>1.7</td>\n",
       "      <td>Ranged</td>\n",
       "      <td>18</td>\n",
       "      <td>2.0</td>\n",
       "      <td>43</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>21</td>\n",
       "      <td>True</td>\n",
       "      <td>3.3</td>\n",
       "      <td>2</td>\n",
       "      <td>290</td>\n",
       "      <td>int</td>\n",
       "      <td>1125</td>\n",
       "      <td>2.6</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      name       localized_name  \\\n",
       "hero_id                                                           \n",
       "45                     npc_dota_hero_pugna                Pugna   \n",
       "62             npc_dota_hero_bounty_hunter        Bounty Hunter   \n",
       "90       npc_dota_hero_keeper_of_the_light  Keeper of the Light   \n",
       "129                     npc_dota_hero_mars                 Mars   \n",
       "53                    npc_dota_hero_furion     Nature's Prophet   \n",
       "\n",
       "                                                     roles  agi_gain  \\\n",
       "hero_id                                                                \n",
       "45                                     ['Nuker', 'Pusher']       1.0   \n",
       "62                                     ['Escape', 'Nuker']       2.6   \n",
       "90             ['Support', 'Nuker', 'Disabler', 'Jungler']       1.6   \n",
       "129          ['Carry', 'Initiator', 'Disabler', 'Durable']       1.9   \n",
       "53       ['Carry', 'Jungler', 'Pusher', 'Escape', 'Nuker']       3.3   \n",
       "\n",
       "         attack_range  attack_rate attack_type  base_agi  base_armor  \\\n",
       "hero_id                                                                \n",
       "45                630          1.7      Ranged        16         0.0   \n",
       "62                150          1.7       Melee        21         3.0   \n",
       "90                600          1.7      Ranged        15        -1.0   \n",
       "129               250          1.8       Melee        20         0.0   \n",
       "53                600          1.7      Ranged        18         2.0   \n",
       "\n",
       "         base_attack_max    ...      base_mr  base_str  cm_enabled  int_gain  \\\n",
       "hero_id                     ...                                                \n",
       "45                    27    ...           25        19        True       5.2   \n",
       "62                    38    ...           25        20        True       2.0   \n",
       "90                    27    ...           25        16        True       3.2   \n",
       "129                   43    ...           25        23       False       1.4   \n",
       "53                    43    ...           25        21        True       3.3   \n",
       "\n",
       "         legs  move_speed  primary_attr  projectile_speed  str_gain  turn_rate  \n",
       "hero_id                                                                         \n",
       "45          2         330           int               900       2.0        0.5  \n",
       "62          2         315           agi               900       2.5        0.6  \n",
       "90          2         330           int               900       2.3        0.5  \n",
       "129         2         310           str               900       3.6        0.8  \n",
       "53          2         290           int              1125       2.6        0.6  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_heroes.loc[record['dire_heroes'], :]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Решение 1: \"Заглушка\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "В обучающей выборке больше неопытных игроков, чем опытных:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:39.791844Z",
     "start_time": "2019-03-08T17:10:39.778677Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    60085\n",
       "1    39786\n",
       "Name: skilled, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train['skilled'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "В случае, если мы не имеем никакой информации об игроке, имеет смысл предсказывать что он _неопытный_. Основываясь на этом принципе, можем построить первое решение: для всех тестовых примеров определять игрока как _неопытного_.\n",
    "\n",
    "Оценим точность такого предсказания на обучающей выборке (доля угаданных значений целевой переменной): "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:39.809915Z",
     "start_time": "2019-03-08T17:10:39.799940Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train accuracy: 0.6016260976659892\n"
     ]
    }
   ],
   "source": [
    "dummy_accuracy = (df_train['skilled'] == 0).mean()\n",
    "print('Train accuracy:', dummy_accuracy)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Запишем предсказания в CSV-файл `sample_submission.csv`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:39.951282Z",
     "start_time": "2019-03-08T17:10:39.813223Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>skilled</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    skilled\n",
       "id         \n",
       "0         0\n",
       "1         0\n",
       "4         0\n",
       "5         0\n",
       "9         0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_submission_dummy = pandas.DataFrame({'skilled': 0}, index=df_test.index)\n",
    "df_submission_dummy.to_csv('sample_submission.csv')\n",
    "df_submission_dummy.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Эти предсказания можно отправлять в проверяющую систему."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Решение 2: Находим закономерность\n",
    "\n",
    "Если посмотреть на распределения различных переменных по опытным и неопытным игрокам, то можно обнаружить, что игроки с достаточно высоким `avg_gpm_x16` как правило опытные:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:40.909281Z",
     "start_time": "2019-03-08T17:10:39.954330Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1114ab9e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "selected_column = 'avg_gpm_x16'\n",
    "threshold = 530\n",
    "\n",
    "figure(figsize=(12, 4))\n",
    "df_train.loc[df_train.skilled == 1, selected_column].hist(bins=100, alpha=0.5)\n",
    "df_train.loc[df_train.skilled == 0, selected_column].hist(bins=100, alpha=0.5)\n",
    "legend(['skilled', 'not skilled'])\n",
    "plot([threshold, threshold], [0, 1000])\n",
    "_ = title('Histogram of {}'.format(selected_column))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Используя это наблюдения, можно построить более точное решение:\n",
    "- если `avg_gpm_x16 > 530` => вероятно игрок опытный, предсказываем `skilled=1`\n",
    "- иначе => скорее всего неопытный, предсказываем `skilled=0`\n",
    "\n",
    "Используя этот алгоритм, построим предсказания для обучающей и тестовой выборок:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:40.929118Z",
     "start_time": "2019-03-08T17:10:40.915897Z"
    }
   },
   "outputs": [],
   "source": [
    "skilled_train_pred = (df_train[selected_column] > threshold).astype(int)\n",
    "skilled_test_pred = (df_test[selected_column] > threshold).astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Оценим качество получившегося решения (долю примеров с правильно угаданным `skilled`) на обучающей выборке:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:40.954474Z",
     "start_time": "2019-03-08T17:10:40.935437Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train accuracy: 0.6377927526509197\n"
     ]
    }
   ],
   "source": [
    "print('Train accuracy:', (skilled_train_pred == df_train['skilled']).mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Доля правильных предсказаний существенно выше чем в решении-\"заглушке\". Сохраним предсказания в CSV-файл, который можно отправлять в систему:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:41.125831Z",
     "start_time": "2019-03-08T17:10:40.957355Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>skilled</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>193369</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193372</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193375</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193389</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193391</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193392</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193393</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193402</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193410</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193411</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        skilled\n",
       "id             \n",
       "193369        1\n",
       "193372        0\n",
       "193375        0\n",
       "193389        0\n",
       "193391        0\n",
       "193392        0\n",
       "193393        0\n",
       "193402        0\n",
       "193410        1\n",
       "193411        0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_submission_rule = pandas.DataFrame({'skilled': skilled_test_pred})\n",
    "df_submission_rule.to_csv('submission_rule.csv')\n",
    "df_submission_rule.tail(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Решение 3: Дерево решений"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dummy-решение с константным ответом и решение на основе одного признака получились лучше, чем случайное решение, но можно двигаться дальше. Одним из простых алгоритмов машинного обучения дерево решений. Основная идея в разделении объектов выборки на основе простых правил так, чтобы каждой группе сопоставить некоторый ответ."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Матрица объект-признак\n",
    "\n",
    "Исключим из обучающей выборки целевую переменную и два строковых признака."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:41.224623Z",
     "start_time": "2019-03-08T17:10:41.130575Z"
    }
   },
   "outputs": [],
   "source": [
    "X = df_train.drop(columns=['skilled', 'player_team', 'winner_team'])\n",
    "X_test = df_test.drop(columns=['player_team', 'winner_team'])\n",
    "y = df_train['skilled']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Построение решающего дерева\n",
    "\n",
    "Обучением решающее дерево глубины 4. На визуализации можно увидеть, какие правила для разделения выборки были получены."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:43.886458Z",
     "start_time": "2019-03-08T17:10:41.236995Z"
    }
   },
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "tree_classifier = DecisionTreeClassifier(max_depth=4).fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:44.549919Z",
     "start_time": "2019-03-08T17:10:43.889908Z"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.tree import export_graphviz\n",
    "export_graphviz(\n",
    "    tree_classifier,\n",
    "    out_file='skill_tree.dot',\n",
    "    feature_names=X.columns,\n",
    "    filled=True,\n",
    "    proportion=True,\n",
    "    rounded=True,\n",
    "    impurity=False,\n",
    ")\n",
    "!dot -Tpng skill_tree.dot -o skill_tree.png\n",
    "\n",
    "from IPython.display import Image\n",
    "Image('skill_tree.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Предсказания на тестовой выборке"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Сделаем предсказание деревом решений на тестовой выборке и сохраним предсказания в файл."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:44.747405Z",
     "start_time": "2019-03-08T17:10:44.552600Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>skilled</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>193392</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193393</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193402</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193410</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193411</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        skilled\n",
       "id             \n",
       "193392        0\n",
       "193393        0\n",
       "193402        0\n",
       "193410        0\n",
       "193411        0"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred = tree_classifier.predict(X_test)\n",
    "df_submission_tree = pandas.DataFrame({'skilled': y_pred}, index=df_test.index)\n",
    "df_submission_tree.to_csv('submission_tree.csv')\n",
    "df_submission_tree.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Оценка качества на обучающей выборке"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:44.833673Z",
     "start_time": "2019-03-08T17:10:44.751404Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train accuracy: 0.659701014308458\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "print('Train accuracy:', accuracy_score(y, tree_classifier.predict(X)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Оценка качества методом кросс-валидации\n",
    "\n",
    "Оценка качества модели на обучающей выборке некорректна, так как мы оцениваем качество алгоритма, который видел правильные ответы (и мог их запомнить). Для избежения этого используют кросс-валидацию, то есть оценивают качество алгоритма на частях обучающей выборки, которую не видел алгоритм при обучении."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:50.982020Z",
     "start_time": "2019-03-08T17:10:44.836569Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation accuracy: 0.6575282113926966\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import cross_val_predict\n",
    "\n",
    "y_pred = cross_val_predict(\n",
    "    DecisionTreeClassifier(max_depth=4),\n",
    "    X, y,\n",
    "    cv=5,\n",
    "    n_jobs=-1,\n",
    ")\n",
    "\n",
    "print('Validation accuracy:', accuracy_score(df_train['skilled'], y_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Идеи по дальнейшему улучшению точности решения"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Подбор параметров модели\n",
    "\n",
    "Для получения более высокого качества часто необходимо подобрать значения параметров алгоритма. Например, у решающего дерева есть параметр глубина дерева `max_depth`. Увеличим значение с 4 до 8. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:10:57.423982Z",
     "start_time": "2019-03-08T17:10:50.985775Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation accuracy: 0.6730181934695757\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import cross_val_predict\n",
    "\n",
    "y_pred = cross_val_predict(\n",
    "    DecisionTreeClassifier(max_depth=8),\n",
    "    X, y,\n",
    "    cv=5,\n",
    "    n_jobs=-1,\n",
    ")\n",
    "\n",
    "print('Validation accuracy:', accuracy_score(df_train['skilled'], y_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Качество алгоритма выросло!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Использование различных алгоритмов машинного обучения\n",
    "\n",
    "Решающие деревья — один из методов машинного обучения, есть много других алгоритмов, которые при правильном использовании могут дать лучший результат. Воспользуемся, например, случайным лесом — множеством решающих деревьев, ответы которых усредняются."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:13:07.143663Z",
     "start_time": "2019-03-08T17:10:57.427369Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation accuracy: 0.7155230247018654\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "y_pred = cross_val_predict(\n",
    "    RandomForestClassifier(n_estimators=100),\n",
    "    X, y,\n",
    "    cv=5,\n",
    "    n_jobs=-1,\n",
    ")\n",
    "\n",
    "print('Validation accuracy:', accuracy_score(df_train['skilled'], y_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Использование категориальных признаков\n",
    "\n",
    "В нашей выборке есть числовые признаки, которые по смыслу означают категории. Например, герой, за которого играл человек. Посмотрим на различия в `avg_gpm_x16` у двух типов героев. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:13:08.004200Z",
     "start_time": "2019-03-08T17:13:07.147255Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11070c7b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "selected_heroes = [(8, 'Juggernaut'), (74, 'Invoker')]\n",
    "\n",
    "figure(figsize=(12, 8))\n",
    "for i, (selected_hero, hero_name) in enumerate(selected_heroes):\n",
    "    subplot(len(selected_heroes), 1, i+1)\n",
    "    df_train.loc[(df_train.skilled == 1) & (df_train.hero_id == selected_hero), selected_column].hist(bins=50, alpha=0.5)\n",
    "    df_train.loc[(df_train.skilled == 0) & (df_train.hero_id == selected_hero), selected_column].hist(bins=50, alpha=0.5)\n",
    "    xlim([300, 700])\n",
    "    legend(['skilled', 'not skilled'])\n",
    "    title(hero_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Большинство алгоритмов машинного обучения не понимает, что признак по смыслу категориальный, а считает его числом. Поэтому попробуем добавить признаки `играл за героя X` для всех возможных героев."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:14:48.705283Z",
     "start_time": "2019-03-08T17:13:08.008052Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation accuracy: 0.7161338126182776\n"
     ]
    }
   ],
   "source": [
    "for hero_id in set(df_train.hero_id):\n",
    "    df_train['is_hero_{}'.format(hero_id)] = df_train.hero_id == hero_id\n",
    "    df_test['is_hero_{}'.format(hero_id)] = df_test.hero_id == hero_id\n",
    "\n",
    "X = df_train.drop(columns=['skilled', 'player_team', 'winner_team'])\n",
    "X_test = df_test.drop(columns=['player_team', 'winner_team'])\n",
    "y = df_train['skilled']\n",
    "\n",
    "y_pred = cross_val_predict(\n",
    "    RandomForestClassifier(n_estimators=100),\n",
    "    X, y,\n",
    "    cv=5,\n",
    "    n_jobs=-1,\n",
    ")\n",
    "\n",
    "print('Validation accuracy:', accuracy_score(df_train['skilled'], y_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Использование расширенного набора данных, создание новых признаков"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Как уже говорилось, есть дополнительная информация о героях, умениях и предметах. Можно сгенерировать новые признаки на их основе. \n",
    "\n",
    "Посчитаем, каких типов умения применялись игроков и в каком количестве. Для этого нужно воспользовать большой версией данных (это займёт некоторое время)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:14:48.743507Z",
     "start_time": "2019-03-08T17:14:48.708889Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>dname</th>\n",
       "      <th>behavior</th>\n",
       "      <th>desc</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ability_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5003</th>\n",
       "      <td>antimage_mana_break</td>\n",
       "      <td>Passive</td>\n",
       "      <td>Burns an opponent's mana on each attack.  Mana...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5004</th>\n",
       "      <td>antimage_blink</td>\n",
       "      <td>Point Target</td>\n",
       "      <td>Short distance teleportation that allows Anti-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5005</th>\n",
       "      <td>antimage_spell_shield</td>\n",
       "      <td>Passive</td>\n",
       "      <td>Increases Anti-Mage's resistance to magic dama...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7314</th>\n",
       "      <td>antimage_counterspell</td>\n",
       "      <td>No Target</td>\n",
       "      <td>Passively grants you magic resistance. Can be ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5006</th>\n",
       "      <td>antimage_mana_void</td>\n",
       "      <td>Unit Target</td>\n",
       "      <td>For each point of mana missing by the target u...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            dname      behavior  \\\n",
       "ability_id                                        \n",
       "5003          antimage_mana_break       Passive   \n",
       "5004               antimage_blink  Point Target   \n",
       "5005        antimage_spell_shield       Passive   \n",
       "7314        antimage_counterspell     No Target   \n",
       "5006           antimage_mana_void   Unit Target   \n",
       "\n",
       "                                                         desc  \n",
       "ability_id                                                     \n",
       "5003        Burns an opponent's mana on each attack.  Mana...  \n",
       "5004        Short distance teleportation that allows Anti-...  \n",
       "5005        Increases Anti-Mage's resistance to magic dama...  \n",
       "7314        Passively grants you magic resistance. Can be ...  \n",
       "5006        For each point of mana missing by the target u...  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_abilities = pandas.read_csv('data/dota2_abilities.csv', index_col='ability_id')\n",
    "df_abilities.behavior = df_abilities.behavior.apply(\n",
    "    lambda x: x.split(\"'\")).apply(lambda x: x[1] if len(x) > 1 else 'empty')\n",
    "df_abilities.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:49:19.028519Z",
     "start_time": "2019-03-08T17:14:48.747066Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e2614145bdab45b7b441011d50d2c245",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "58d90912972545ad98f8fc7461487d35",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "import tqdm\n",
    "\n",
    "for ability_behavior in set(df_abilities.behavior.fillna('empty')):\n",
    "    df_train['upgrade_behavior {}'.format(ability_behavior)] = 0\n",
    "    df_test['upgrade_behavior {}'.format(ability_behavior)] = 0\n",
    "    \n",
    "with open('data/dota2_skill_train.jsonlines') as fin:\n",
    "    for line in tqdm.tqdm_notebook(fin):\n",
    "        record = json.loads(line)\n",
    "        for ability_upgrade in record['ability_upgrades']:\n",
    "            df_train.loc[record['id'], 'upgrade_behavior {}'.format(\n",
    "                df_abilities.loc[ability_upgrade, 'behavior'])] += 1\n",
    "            \n",
    "with open('data/dota2_skill_test.jsonlines') as fin:\n",
    "    for line in tqdm.tqdm_notebook(fin):\n",
    "        record = json.loads(line)\n",
    "        for ability_upgrade in record['ability_upgrades']:\n",
    "            df_test.loc[record['id'], 'upgrade_behavior {}'.format(\n",
    "                df_abilities.loc[ability_upgrade, 'behavior'])] += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:50:56.812568Z",
     "start_time": "2019-03-08T17:49:19.031044Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation accuracy: 0.7206296121997376\n"
     ]
    }
   ],
   "source": [
    "X = df_train.drop(columns=['skilled', 'player_team', 'winner_team'])\n",
    "X_test = df_test.drop(columns=['player_team', 'winner_team'])\n",
    "y = df_train['skilled']\n",
    "\n",
    "y_pred = cross_val_predict(\n",
    "    RandomForestClassifier(n_estimators=100),\n",
    "    X, y,\n",
    "    cv=5,\n",
    "    n_jobs=-1,\n",
    ")\n",
    "\n",
    "print('Validation accuracy:', accuracy_score(df_train['skilled'], y_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ансамблирование моделей"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Один алгоритм хорошо, а несколько могут решить задачу лучше (там, где один не уверен, другой может дать правильный ответ). Возьмём к случайному лесу градиентный бустинг (ещё один алгоритм на основе решающих деревьев), предскажем с помощью них степень уверенности в `1` (вероятность того, что игрок `skilled`). Усредним их и переведём в предсказание классов."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:50:56.822006Z",
     "start_time": "2019-03-08T17:50:56.816836Z"
    }
   },
   "outputs": [],
   "source": [
    "from sklearn.ensemble import GradientBoostingClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:56:03.940993Z",
     "start_time": "2019-03-08T17:50:56.825885Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation accuracy RF: 0.7197084238667881\n",
      "Validation accuracy GB: 0.7159135284517028\n",
      "Validation accuracy RF+GB: 0.722902544282124\n"
     ]
    }
   ],
   "source": [
    "X = df_train.drop(columns=['skilled', 'player_team', 'winner_team'])\n",
    "X_test = df_test.drop(columns=['player_team', 'winner_team'])\n",
    "y = df_train['skilled']\n",
    "\n",
    "y_pred_rf = cross_val_predict(\n",
    "    RandomForestClassifier(n_estimators=100),\n",
    "    X, y,\n",
    "    cv=5,\n",
    "    n_jobs=-1,\n",
    "    method='predict_proba'\n",
    ")[:, 1]\n",
    "\n",
    "y_pred_gb = cross_val_predict(\n",
    "    GradientBoostingClassifier(),\n",
    "    X, y,\n",
    "    cv=5,\n",
    "    n_jobs=-1,\n",
    "    method='predict_proba'\n",
    ")[:, 1]\n",
    "\n",
    "y_pred = 0.5 * y_pred_rf + 0.5 * y_pred_gb\n",
    "\n",
    "print('Validation accuracy RF:', accuracy_score(df_train['skilled'], y_pred_rf > 0.5))\n",
    "print('Validation accuracy GB:', accuracy_score(df_train['skilled'], y_pred_gb > 0.5))\n",
    "print('Validation accuracy RF+GB:', accuracy_score(df_train['skilled'], y_pred > 0.5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Сохраним таблицу с предсказаниями."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T17:58:01.592810Z",
     "start_time": "2019-03-08T17:56:03.943395Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>skilled</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>193392</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193393</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193402</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193410</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193411</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        skilled\n",
       "id             \n",
       "193392        0\n",
       "193393        0\n",
       "193402        0\n",
       "193410        0\n",
       "193411        0"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_rf = RandomForestClassifier(n_estimators=100)\n",
    "model_rf.fit(X, y)\n",
    "y_pred_rf = model_rf.predict_proba(X_test)[:, 1]\n",
    "\n",
    "model_gb = GradientBoostingClassifier()\n",
    "model_gb.fit(X, y)\n",
    "y_pred_gb = model_gb.predict_proba(X_test)[:, 1]\n",
    "\n",
    "y_pred = ((0.5 * y_pred_rf + 0.5 * y_pred_gb) > 0.5).astype(int)\n",
    "df_submission = pandas.DataFrame({'skilled': y_pred}, index=df_test.index)\n",
    "df_submission.to_csv('submission_ensemble.csv')\n",
    "df_submission.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Использовать опыт решения других соревнований\n",
    "\n",
    "[YouTube: Тренировки по машинному обучению](https://www.youtube.com/channel/UCeq6ZIlvC9SVsfhfKnSvM9w)\n",
    "\n",
    "[Материалы Академии Искусственного Интеллекта 2018](http://contest.ai-academy.ru/description)\n",
    "\n",
    "[YouTube: Александр Мамаев — Предсказание победы команды в матче Dota2](https://www.youtube.com/watch?v=YSQqHlQwQDY&t=50s)"
   ]
  }
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