9장/9.6 아이템 기반 인접 이웃 협업 필터링 실습.ipynb

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   "outputs": [
    {
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     "output_type": "stream",
     "text": [
      "(9742, 3)\n",
      "(100836, 4)\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "movies = pd.read_csv('./ml-latest-small/movies.csv')\n",
    "ratings = pd.read_csv('./ml-latest-small/ratings.csv')\n",
    "print(movies.shape)\n",
    "print(ratings.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
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       "      <th>movieId</th>\n",
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       "      <td>Toy Story (1995)</td>\n",
       "      <td>Adventure|Animation|Children|Comedy|Fantasy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Jumanji (1995)</td>\n",
       "      <td>Adventure|Children|Fantasy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Grumpier Old Men (1995)</td>\n",
       "      <td>Comedy|Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Waiting to Exhale (1995)</td>\n",
       "      <td>Comedy|Drama|Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Father of the Bride Part II (1995)</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   movieId                               title  \\\n",
       "0        1                    Toy Story (1995)   \n",
       "1        2                      Jumanji (1995)   \n",
       "2        3             Grumpier Old Men (1995)   \n",
       "3        4            Waiting to Exhale (1995)   \n",
       "4        5  Father of the Bride Part II (1995)   \n",
       "\n",
       "                                        genres  \n",
       "0  Adventure|Animation|Children|Comedy|Fantasy  \n",
       "1                   Adventure|Children|Fantasy  \n",
       "2                               Comedy|Romance  \n",
       "3                         Comedy|Drama|Romance  \n",
       "4                                       Comedy  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
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       "   userId  movieId  rating  timestamp\n",
       "0       1        1     4.0  964982703\n",
       "1       1        3     4.0  964981247\n",
       "2       1        6     4.0  964982224\n",
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     "execution_count": 3,
     "metadata": {},
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   ],
   "source": [
    "ratings.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "movieId  1       2       3       4       5       6       7       8       \\\n",
       "userId                                                                    \n",
       "1           4.0     NaN     4.0     NaN     NaN     4.0     NaN     NaN   \n",
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       "\n",
       "movieId  9       10      ...  193565  193567  193571  193573  193579  193581  \\\n",
       "userId                   ...                                                   \n",
       "1           NaN     NaN  ...     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "2           NaN     NaN  ...     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "3           NaN     NaN  ...     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "\n",
       "movieId  193583  193585  193587  193609  \n",
       "userId                                   \n",
       "1           NaN     NaN     NaN     NaN  \n",
       "2           NaN     NaN     NaN     NaN  \n",
       "3           NaN     NaN     NaN     NaN  \n",
       "\n",
       "[3 rows x 9724 columns]"
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     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings = ratings[['userId', 'movieId', 'rating']]\n",
    "ratings_matrix = ratings.pivot_table('rating', index='userId', columns='movieId')\n",
    "ratings_matrix.head(3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "      <th>title</th>\n",
       "      <th>'71 (2014)</th>\n",
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       "      <th>'Round Midnight (1986)</th>\n",
       "      <th>'Salem's Lot (2004)</th>\n",
       "      <th>'Til There Was You (1997)</th>\n",
       "      <th>'Tis the Season for Love (2015)</th>\n",
       "      <th>'burbs, The (1989)</th>\n",
       "      <th>'night Mother (1986)</th>\n",
       "      <th>(500) Days of Summer (2009)</th>\n",
       "      <th>*batteries not included (1987)</th>\n",
       "      <th>...</th>\n",
       "      <th>Zulu (2013)</th>\n",
       "      <th>[REC] (2007)</th>\n",
       "      <th>[REC]² (2009)</th>\n",
       "      <th>[REC]³ 3 Génesis (2012)</th>\n",
       "      <th>anohana: The Flower We Saw That Day - The Movie (2013)</th>\n",
       "      <th>eXistenZ (1999)</th>\n",
       "      <th>xXx (2002)</th>\n",
       "      <th>xXx: State of the Union (2005)</th>\n",
       "      <th>¡Three Amigos! (1986)</th>\n",
       "      <th>À nous la liberté (Freedom for Us) (1931)</th>\n",
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       "title   '71 (2014)  'Hellboy': The Seeds of Creation (2004)  \\\n",
       "userId                                                        \n",
       "1              0.0                                      0.0   \n",
       "2              0.0                                      0.0   \n",
       "3              0.0                                      0.0   \n",
       "\n",
       "title   'Round Midnight (1986)  'Salem's Lot (2004)  \\\n",
       "userId                                                \n",
       "1                          0.0                  0.0   \n",
       "2                          0.0                  0.0   \n",
       "3                          0.0                  0.0   \n",
       "\n",
       "title   'Til There Was You (1997)  'Tis the Season for Love (2015)  \\\n",
       "userId                                                               \n",
       "1                             0.0                              0.0   \n",
       "2                             0.0                              0.0   \n",
       "3                             0.0                              0.0   \n",
       "\n",
       "title   'burbs, The (1989)  'night Mother (1986)  (500) Days of Summer (2009)  \\\n",
       "userId                                                                          \n",
       "1                      0.0                   0.0                          0.0   \n",
       "2                      0.0                   0.0                          0.0   \n",
       "3                      0.0                   0.0                          0.0   \n",
       "\n",
       "title   *batteries not included (1987)  ...  Zulu (2013)  [REC] (2007)  \\\n",
       "userId                                  ...                              \n",
       "1                                  0.0  ...          0.0           0.0   \n",
       "2                                  0.0  ...          0.0           0.0   \n",
       "3                                  0.0  ...          0.0           0.0   \n",
       "\n",
       "title   [REC]² (2009)  [REC]³ 3 Génesis (2012)  \\\n",
       "userId                                           \n",
       "1                 0.0                      0.0   \n",
       "2                 0.0                      0.0   \n",
       "3                 0.0                      0.0   \n",
       "\n",
       "title   anohana: The Flower We Saw That Day - The Movie (2013)  \\\n",
       "userId                                                           \n",
       "1                                                     0.0        \n",
       "2                                                     0.0        \n",
       "3                                                     0.0        \n",
       "\n",
       "title   eXistenZ (1999)  xXx (2002)  xXx: State of the Union (2005)  \\\n",
       "userId                                                                \n",
       "1                   0.0         0.0                             0.0   \n",
       "2                   0.0         0.0                             0.0   \n",
       "3                   0.0         0.0                             0.0   \n",
       "\n",
       "title   ¡Three Amigos! (1986)  À nous la liberté (Freedom for Us) (1931)  \n",
       "userId                                                                    \n",
       "1                         4.0                                        0.0  \n",
       "2                         0.0                                        0.0  \n",
       "3                         0.0                                        0.0  \n",
       "\n",
       "[3 rows x 9719 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# title 컬럼을 얻기 이해 movies 와 조인 수행\n",
    "rating_movies = pd.merge(ratings, movies, on='movieId')\n",
    "\n",
    "# columns='title' 로 title 컬럼으로 pivot 수행. \n",
    "ratings_matrix = rating_movies.pivot_table('rating', index='userId', columns='title')\n",
    "\n",
    "# NaN 값을 모두 0 으로 변환\n",
    "ratings_matrix = ratings_matrix.fillna(0)\n",
    "ratings_matrix.head(3)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 영화와 영화들 간 유사도 산출"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>userId</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
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       "      <th>4</th>\n",
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       "      <th>10</th>\n",
       "      <th>...</th>\n",
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       "      <th>602</th>\n",
       "      <th>603</th>\n",
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       "      <th>609</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "  <tbody>\n",
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       "      <th>'71 (2014)</th>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>'Hellboy': The Seeds of Creation (2004)</th>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>'Round Midnight (1986)</th>\n",
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       "      <td>0.0</td>\n",
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      ],
      "text/plain": [
       "userId                                   1    2    3    4    5    6    7    \\\n",
       "title                                                                        \n",
       "'71 (2014)                               0.0  0.0  0.0  0.0  0.0  0.0  0.0   \n",
       "'Hellboy': The Seeds of Creation (2004)  0.0  0.0  0.0  0.0  0.0  0.0  0.0   \n",
       "'Round Midnight (1986)                   0.0  0.0  0.0  0.0  0.0  0.0  0.0   \n",
       "\n",
       "userId                                   8    9    10   ...  601  602  603  \\\n",
       "title                                                   ...                  \n",
       "'71 (2014)                               0.0  0.0  0.0  ...  0.0  0.0  0.0   \n",
       "'Hellboy': The Seeds of Creation (2004)  0.0  0.0  0.0  ...  0.0  0.0  0.0   \n",
       "'Round Midnight (1986)                   0.0  0.0  0.0  ...  0.0  0.0  0.0   \n",
       "\n",
       "userId                                   604  605  606  607  608  609  610  \n",
       "title                                                                       \n",
       "'71 (2014)                               0.0  0.0  0.0  0.0  0.0  0.0  4.0  \n",
       "'Hellboy': The Seeds of Creation (2004)  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
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       "\n",
       "[3 rows x 610 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings_matrix_T = ratings_matrix.transpose()\n",
    "ratings_matrix_T.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(9719, 9719)\n"
     ]
    },
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       "title                                    '71 (2014)  \\\n",
       "title                                                 \n",
       "'71 (2014)                                      1.0   \n",
       "'Hellboy': The Seeds of Creation (2004)         0.0   \n",
       "'Round Midnight (1986)                          0.0   \n",
       "\n",
       "title                                    'Hellboy': The Seeds of Creation (2004)  \\\n",
       "title                                                                              \n",
       "'71 (2014)                                                              0.000000   \n",
       "'Hellboy': The Seeds of Creation (2004)                                 1.000000   \n",
       "'Round Midnight (1986)                                                  0.707107   \n",
       "\n",
       "title                                    'Round Midnight (1986)  \\\n",
       "title                                                             \n",
       "'71 (2014)                                             0.000000   \n",
       "'Hellboy': The Seeds of Creation (2004)                0.707107   \n",
       "'Round Midnight (1986)                                 1.000000   \n",
       "\n",
       "title                                    'Salem's Lot (2004)  \\\n",
       "title                                                          \n",
       "'71 (2014)                                               0.0   \n",
       "'Hellboy': The Seeds of Creation (2004)                  0.0   \n",
       "'Round Midnight (1986)                                   0.0   \n",
       "\n",
       "title                                    'Til There Was You (1997)  \\\n",
       "title                                                                \n",
       "'71 (2014)                                                     0.0   \n",
       "'Hellboy': The Seeds of Creation (2004)                        0.0   \n",
       "'Round Midnight (1986)                                         0.0   \n",
       "\n",
       "title                                    'Tis the Season for Love (2015)  \\\n",
       "title                                                                      \n",
       "'71 (2014)                                                           0.0   \n",
       "'Hellboy': The Seeds of Creation (2004)                              0.0   \n",
       "'Round Midnight (1986)                                               0.0   \n",
       "\n",
       "title                                    'burbs, The (1989)  \\\n",
       "title                                                         \n",
       "'71 (2014)                                         0.000000   \n",
       "'Hellboy': The Seeds of Creation (2004)            0.000000   \n",
       "'Round Midnight (1986)                             0.176777   \n",
       "\n",
       "title                                    'night Mother (1986)  \\\n",
       "title                                                           \n",
       "'71 (2014)                                                0.0   \n",
       "'Hellboy': The Seeds of Creation (2004)                   0.0   \n",
       "'Round Midnight (1986)                                    0.0   \n",
       "\n",
       "title                                    (500) Days of Summer (2009)  \\\n",
       "title                                                                  \n",
       "'71 (2014)                                                  0.141653   \n",
       "'Hellboy': The Seeds of Creation (2004)                     0.000000   \n",
       "'Round Midnight (1986)                                      0.000000   \n",
       "\n",
       "title                                    *batteries not included (1987)  ...  \\\n",
       "title                                                                    ...   \n",
       "'71 (2014)                                                          0.0  ...   \n",
       "'Hellboy': The Seeds of Creation (2004)                             0.0  ...   \n",
       "'Round Midnight (1986)                                              0.0  ...   \n",
       "\n",
       "title                                    Zulu (2013)  [REC] (2007)  \\\n",
       "title                                                                \n",
       "'71 (2014)                                       0.0      0.342055   \n",
       "'Hellboy': The Seeds of Creation (2004)          0.0      0.000000   \n",
       "'Round Midnight (1986)                           0.0      0.000000   \n",
       "\n",
       "title                                    [REC]² (2009)  \\\n",
       "title                                                    \n",
       "'71 (2014)                                    0.543305   \n",
       "'Hellboy': The Seeds of Creation (2004)       0.000000   \n",
       "'Round Midnight (1986)                        0.000000   \n",
       "\n",
       "title                                    [REC]³ 3 Génesis (2012)  \\\n",
       "title                                                              \n",
       "'71 (2014)                                              0.707107   \n",
       "'Hellboy': The Seeds of Creation (2004)                 0.000000   \n",
       "'Round Midnight (1986)                                  0.000000   \n",
       "\n",
       "title                                    anohana: The Flower We Saw That Day - The Movie (2013)  \\\n",
       "title                                                                                             \n",
       "'71 (2014)                                                                             0.0        \n",
       "'Hellboy': The Seeds of Creation (2004)                                                0.0        \n",
       "'Round Midnight (1986)                                                                 0.0        \n",
       "\n",
       "title                                    eXistenZ (1999)  xXx (2002)  \\\n",
       "title                                                                  \n",
       "'71 (2014)                                           0.0    0.139431   \n",
       "'Hellboy': The Seeds of Creation (2004)              0.0    0.000000   \n",
       "'Round Midnight (1986)                               0.0    0.000000   \n",
       "\n",
       "title                                    xXx: State of the Union (2005)  \\\n",
       "title                                                                     \n",
       "'71 (2014)                                                     0.327327   \n",
       "'Hellboy': The Seeds of Creation (2004)                        0.000000   \n",
       "'Round Midnight (1986)                                         0.000000   \n",
       "\n",
       "title                                    ¡Three Amigos! (1986)  \\\n",
       "title                                                            \n",
       "'71 (2014)                                                 0.0   \n",
       "'Hellboy': The Seeds of Creation (2004)                    0.0   \n",
       "'Round Midnight (1986)                                     0.0   \n",
       "\n",
       "title                                    À nous la liberté (Freedom for Us) (1931)  \n",
       "title                                                                               \n",
       "'71 (2014)                                                                     0.0  \n",
       "'Hellboy': The Seeds of Creation (2004)                                        0.0  \n",
       "'Round Midnight (1986)                                                         0.0  \n",
       "\n",
       "[3 rows x 9719 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "\n",
    "item_sim = cosine_similarity(ratings_matrix_T, ratings_matrix_T)\n",
    "\n",
    "# cosine_similarity() 로 반환된 넘파이 행렬을 영화명을 매핑하여 DataFrame으로 변환\n",
    "item_sim_df = pd.DataFrame(data=item_sim, index=ratings_matrix.columns,\n",
    "                          columns=ratings_matrix.columns)\n",
    "print(item_sim_df.shape)\n",
    "item_sim_df.head(3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title\n",
       "Godfather, The (1972)                        1.000000\n",
       "Godfather: Part II, The (1974)               0.821773\n",
       "Goodfellas (1990)                            0.664841\n",
       "One Flew Over the Cuckoo's Nest (1975)       0.620536\n",
       "Star Wars: Episode IV - A New Hope (1977)    0.595317\n",
       "Fargo (1996)                                 0.588614\n",
       "Name: Godfather, The (1972), dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "item_sim_df[\"Godfather, The (1972)\"].sort_values(ascending=False)[:6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title\n",
       "Dark Knight, The (2008)          0.727263\n",
       "Inglourious Basterds (2009)      0.646103\n",
       "Shutter Island (2010)            0.617736\n",
       "Dark Knight Rises, The (2012)    0.617504\n",
       "Fight Club (1999)                0.615417\n",
       "Name: Inception (2010), dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "item_sim_df[\"Inception (2010)\"].sort_values(ascending=False)[1:6]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 아이템 기반 인접 이웃 협업 필터링으로 개인화된 영화 추천"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict_rating(ratings_arr, item_sim_arr ):\n",
    "    ratings_pred = ratings_arr.dot(item_sim_arr)/ np.array([np.abs(item_sim_arr).sum(axis=1)])\n",
    "    return ratings_pred\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "        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>title</th>\n",
       "      <th>'71 (2014)</th>\n",
       "      <th>'Hellboy': The Seeds of Creation (2004)</th>\n",
       "      <th>'Round Midnight (1986)</th>\n",
       "      <th>'Salem's Lot (2004)</th>\n",
       "      <th>'Til There Was You (1997)</th>\n",
       "      <th>'Tis the Season for Love (2015)</th>\n",
       "      <th>'burbs, The (1989)</th>\n",
       "      <th>'night Mother (1986)</th>\n",
       "      <th>(500) Days of Summer (2009)</th>\n",
       "      <th>*batteries not included (1987)</th>\n",
       "      <th>...</th>\n",
       "      <th>Zulu (2013)</th>\n",
       "      <th>[REC] (2007)</th>\n",
       "      <th>[REC]² (2009)</th>\n",
       "      <th>[REC]³ 3 Génesis (2012)</th>\n",
       "      <th>anohana: The Flower We Saw That Day - The Movie (2013)</th>\n",
       "      <th>eXistenZ (1999)</th>\n",
       "      <th>xXx (2002)</th>\n",
       "      <th>xXx: State of the Union (2005)</th>\n",
       "      <th>¡Three Amigos! (1986)</th>\n",
       "      <th>À nous la liberté (Freedom for Us) (1931)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>userId</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>1</th>\n",
       "      <td>0.070345</td>\n",
       "      <td>0.577855</td>\n",
       "      <td>0.321696</td>\n",
       "      <td>0.227055</td>\n",
       "      <td>0.206958</td>\n",
       "      <td>0.194615</td>\n",
       "      <td>0.249883</td>\n",
       "      <td>0.102542</td>\n",
       "      <td>0.157084</td>\n",
       "      <td>0.178197</td>\n",
       "      <td>...</td>\n",
       "      <td>0.113608</td>\n",
       "      <td>0.181738</td>\n",
       "      <td>0.133962</td>\n",
       "      <td>0.128574</td>\n",
       "      <td>0.006179</td>\n",
       "      <td>0.212070</td>\n",
       "      <td>0.192921</td>\n",
       "      <td>0.136024</td>\n",
       "      <td>0.292955</td>\n",
       "      <td>0.720347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.018260</td>\n",
       "      <td>0.042744</td>\n",
       "      <td>0.018861</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.035995</td>\n",
       "      <td>0.013413</td>\n",
       "      <td>0.002314</td>\n",
       "      <td>0.032213</td>\n",
       "      <td>0.014863</td>\n",
       "      <td>...</td>\n",
       "      <td>0.015640</td>\n",
       "      <td>0.020855</td>\n",
       "      <td>0.020119</td>\n",
       "      <td>0.015745</td>\n",
       "      <td>0.049983</td>\n",
       "      <td>0.014876</td>\n",
       "      <td>0.021616</td>\n",
       "      <td>0.024528</td>\n",
       "      <td>0.017563</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.011884</td>\n",
       "      <td>0.030279</td>\n",
       "      <td>0.064437</td>\n",
       "      <td>0.003762</td>\n",
       "      <td>0.003749</td>\n",
       "      <td>0.002722</td>\n",
       "      <td>0.014625</td>\n",
       "      <td>0.002085</td>\n",
       "      <td>0.005666</td>\n",
       "      <td>0.006272</td>\n",
       "      <td>...</td>\n",
       "      <td>0.006923</td>\n",
       "      <td>0.011665</td>\n",
       "      <td>0.011800</td>\n",
       "      <td>0.012225</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008194</td>\n",
       "      <td>0.007017</td>\n",
       "      <td>0.009229</td>\n",
       "      <td>0.010420</td>\n",
       "      <td>0.084501</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 9719 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "title   '71 (2014)  'Hellboy': The Seeds of Creation (2004)  \\\n",
       "userId                                                        \n",
       "1         0.070345                                 0.577855   \n",
       "2         0.018260                                 0.042744   \n",
       "3         0.011884                                 0.030279   \n",
       "\n",
       "title   'Round Midnight (1986)  'Salem's Lot (2004)  \\\n",
       "userId                                                \n",
       "1                     0.321696             0.227055   \n",
       "2                     0.018861             0.000000   \n",
       "3                     0.064437             0.003762   \n",
       "\n",
       "title   'Til There Was You (1997)  'Tis the Season for Love (2015)  \\\n",
       "userId                                                               \n",
       "1                        0.206958                         0.194615   \n",
       "2                        0.000000                         0.035995   \n",
       "3                        0.003749                         0.002722   \n",
       "\n",
       "title   'burbs, The (1989)  'night Mother (1986)  (500) Days of Summer (2009)  \\\n",
       "userId                                                                          \n",
       "1                 0.249883              0.102542                     0.157084   \n",
       "2                 0.013413              0.002314                     0.032213   \n",
       "3                 0.014625              0.002085                     0.005666   \n",
       "\n",
       "title   *batteries not included (1987)  ...  Zulu (2013)  [REC] (2007)  \\\n",
       "userId                                  ...                              \n",
       "1                             0.178197  ...     0.113608      0.181738   \n",
       "2                             0.014863  ...     0.015640      0.020855   \n",
       "3                             0.006272  ...     0.006923      0.011665   \n",
       "\n",
       "title   [REC]² (2009)  [REC]³ 3 Génesis (2012)  \\\n",
       "userId                                           \n",
       "1            0.133962                 0.128574   \n",
       "2            0.020119                 0.015745   \n",
       "3            0.011800                 0.012225   \n",
       "\n",
       "title   anohana: The Flower We Saw That Day - The Movie (2013)  \\\n",
       "userId                                                           \n",
       "1                                                0.006179        \n",
       "2                                                0.049983        \n",
       "3                                                0.000000        \n",
       "\n",
       "title   eXistenZ (1999)  xXx (2002)  xXx: State of the Union (2005)  \\\n",
       "userId                                                                \n",
       "1              0.212070    0.192921                        0.136024   \n",
       "2              0.014876    0.021616                        0.024528   \n",
       "3              0.008194    0.007017                        0.009229   \n",
       "\n",
       "title   ¡Three Amigos! (1986)  À nous la liberté (Freedom for Us) (1931)  \n",
       "userId                                                                    \n",
       "1                    0.292955                                   0.720347  \n",
       "2                    0.017563                                   0.000000  \n",
       "3                    0.010420                                   0.084501  \n",
       "\n",
       "[3 rows x 9719 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings_pred = predict_rating(ratings_matrix.values , item_sim_df.values)\n",
    "ratings_pred_matrix = pd.DataFrame(data=ratings_pred, index= ratings_matrix.index,\n",
    "                                   columns = ratings_matrix.columns)\n",
    "ratings_pred_matrix.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "아이템 기반 모든 인접 이웃 MSE:  9.895354759094706\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "# 사용자가 평점을 부여한 영화에 대해서만 예측 성능 평가 MSE 를 구함. \n",
    "def get_mse(pred, actual):\n",
    "    # Ignore nonzero terms.\n",
    "    pred = pred[actual.nonzero()].flatten()\n",
    "    actual = actual[actual.nonzero()].flatten()\n",
    "    return mean_squared_error(pred, actual)\n",
    "\n",
    "print('아이템 기반 모든 인접 이웃 MSE: ', get_mse(ratings_pred, ratings_matrix.values ))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict_rating_topsim(ratings_arr, item_sim_arr, n=20):\n",
    "    # 사용자-아이템 평점 행렬 크기만큼 0으로 채운 예측 행렬 초기화\n",
    "    pred = np.zeros(ratings_arr.shape)\n",
    "\n",
    "    # 사용자-아이템 평점 행렬의 열 크기만큼 Loop 수행. \n",
    "    for col in range(ratings_arr.shape[1]):\n",
    "        # 유사도 행렬에서 유사도가 큰 순으로 n개 데이터 행렬의 index 반환\n",
    "        top_n_items = [np.argsort(item_sim_arr[:, col])[:-n-1:-1]]\n",
    "        # 개인화된 예측 평점을 계산\n",
    "        for row in range(ratings_arr.shape[0]):\n",
    "            pred[row, col] = item_sim_arr[col, :][top_n_items].dot(ratings_arr[row, :][top_n_items].T) \n",
    "            pred[row, col] /= np.sum(np.abs(item_sim_arr[col, :][top_n_items]))        \n",
    "    return pred\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\yong\\AppData\\Local\\Temp\\ipykernel_737000\\2430470973.py:11: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  pred[row, col] = item_sim_arr[col, :][top_n_items].dot(ratings_arr[row, :][top_n_items].T)\n",
      "C:\\Users\\yong\\AppData\\Local\\Temp\\ipykernel_737000\\2430470973.py:12: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  pred[row, col] /= np.sum(np.abs(item_sim_arr[col, :][top_n_items]))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "아이템 기반 인접 TOP-20 이웃 MSE:  3.6949999176225483\n"
     ]
    }
   ],
   "source": [
    "ratings_pred = predict_rating_topsim(ratings_matrix.values , item_sim_df.values, n=20)\n",
    "print('아이템 기반 인접 TOP-20 이웃 MSE: ', get_mse(ratings_pred, ratings_matrix.values ))\n",
    "\n",
    "\n",
    "# 계산된 예측 평점 데이터는 DataFrame으로 재생성\n",
    "ratings_pred_matrix = pd.DataFrame(data=ratings_pred, index= ratings_matrix.index,\n",
    "                                   columns = ratings_matrix.columns)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title\n",
       "Adaptation (2002)                                                                 5.0\n",
       "Citizen Kane (1941)                                                               5.0\n",
       "Raiders of the Lost Ark (Indiana Jones and the Raiders of the Lost Ark) (1981)    5.0\n",
       "Producers, The (1968)                                                             5.0\n",
       "Lord of the Rings: The Two Towers, The (2002)                                     5.0\n",
       "Lord of the Rings: The Fellowship of the Ring, The (2001)                         5.0\n",
       "Back to the Future (1985)                                                         5.0\n",
       "Austin Powers in Goldmember (2002)                                                5.0\n",
       "Minority Report (2002)                                                            4.0\n",
       "Witness (1985)                                                                    4.0\n",
       "Name: 9, dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_rating_id = ratings_matrix.loc[9, :]\n",
    "user_rating_id[ user_rating_id > 0].sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_unseen_movies(ratings_matrix, userId):\n",
    "    # userId로 입력받은 사용자의 모든 영화정보 추출하여 Series로 반환함. \n",
    "    # 반환된 user_rating 은 영화명(title)을 index로 가지는 Series 객체임. \n",
    "    user_rating = ratings_matrix.loc[userId,:]\n",
    "    \n",
    "    # user_rating이 0보다 크면 기존에 관람한 영화임. 대상 index를 추출하여 list 객체로 만듬\n",
    "    already_seen = user_rating[ user_rating > 0].index.tolist()\n",
    "    \n",
    "    # 모든 영화명을 list 객체로 만듬. \n",
    "    movies_list = ratings_matrix.columns.tolist()\n",
    "    \n",
    "    # list comprehension으로 already_seen에 해당하는 movie는 movies_list에서 제외함. \n",
    "    unseen_list = [ movie for movie in movies_list if movie not in already_seen]\n",
    "    \n",
    "    return unseen_list\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "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>pred_score</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Shrek (2001)</th>\n",
       "      <td>0.866202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spider-Man (2002)</th>\n",
       "      <td>0.857854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Last Samurai, The (2003)</th>\n",
       "      <td>0.817473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indiana Jones and the Temple of Doom (1984)</th>\n",
       "      <td>0.816626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Matrix Reloaded, The (2003)</th>\n",
       "      <td>0.800990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Harry Potter and the Sorcerer's Stone (a.k.a. Harry Potter and the Philosopher's Stone) (2001)</th>\n",
       "      <td>0.765159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gladiator (2000)</th>\n",
       "      <td>0.740956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Matrix, The (1999)</th>\n",
       "      <td>0.732693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pirates of the Caribbean: The Curse of the Black Pearl (2003)</th>\n",
       "      <td>0.689591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lord of the Rings: The Return of the King, The (2003)</th>\n",
       "      <td>0.676711</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    pred_score\n",
       "title                                                         \n",
       "Shrek (2001)                                          0.866202\n",
       "Spider-Man (2002)                                     0.857854\n",
       "Last Samurai, The (2003)                              0.817473\n",
       "Indiana Jones and the Temple of Doom (1984)           0.816626\n",
       "Matrix Reloaded, The (2003)                           0.800990\n",
       "Harry Potter and the Sorcerer's Stone (a.k.a. H...    0.765159\n",
       "Gladiator (2000)                                      0.740956\n",
       "Matrix, The (1999)                                    0.732693\n",
       "Pirates of the Caribbean: The Curse of the Blac...    0.689591\n",
       "Lord of the Rings: The Return of the King, The ...    0.676711"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def recomm_movie_by_userid(pred_df, userId, unseen_list, top_n=10):\n",
    "    # 예측 평점 DataFrame에서 사용자id index와 unseen_list로 들어온 영화명 컬럼을 추출하여\n",
    "    # 가장 예측 평점이 높은 순으로 정렬함. \n",
    "    recomm_movies = pred_df.loc[userId, unseen_list].sort_values(ascending=False)[:top_n]\n",
    "    return recomm_movies\n",
    "    \n",
    "# 사용자가 관람하지 않는 영화명 추출   \n",
    "unseen_list = get_unseen_movies(ratings_matrix, 9)\n",
    "\n",
    "# 아이템 기반의 인접 이웃 협업 필터링으로 영화 추천 \n",
    "recomm_movies = recomm_movie_by_userid(ratings_pred_matrix, 9, unseen_list, top_n=10)\n",
    "\n",
    "# 평점 데이타를 DataFrame으로 생성. \n",
    "recomm_movies = pd.DataFrame(data=recomm_movies.values,index=recomm_movies.index,columns=['pred_score'])\n",
    "recomm_movies\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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