00_02-generate_recommendations.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d594cfe3-553e-479d-89dc-01d7216a78d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "06b8af3f-a0b6-4966-9c4e-a2b7c1651cc0",
   "metadata": {},
   "outputs": [],
   "source": [
    "from  caserec.recommenders.rating_prediction.svdplusplus import SVDPlusPlus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6939416a-5dd6-4607-88cb-1bafbd2c247b",
   "metadata": {},
   "outputs": [],
   "source": [
    "movielens = pd.read_csv(\"datasets/ml20m_filtered.csv\")[[\"userId\", \"movieId\", \"genres\", \"timestamp\", \"rating\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "a27c3b9e-26c0-4eed-b0a2-f3f1af5679f7",
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "         userId  movieId                                       genres  \\\n",
       "0             3        1  Adventure|Animation|Children|Comedy|Fantasy   \n",
       "1             6        1  Adventure|Animation|Children|Comedy|Fantasy   \n",
       "2             8        1  Adventure|Animation|Children|Comedy|Fantasy   \n",
       "3            10        1  Adventure|Animation|Children|Comedy|Fantasy   \n",
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       "...         ...      ...                                          ...   \n",
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       "9964929  133047   129354                   Comedy|Crime|Drama|Romance   \n",
       "\n",
       "          timestamp  rating  \n",
       "0         944919407     4.0  \n",
       "1         858275452     5.0  \n",
       "2         833981871     4.0  \n",
       "3         943497887     4.0  \n",
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       "\n",
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     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movielens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "b3118fd4-759a-4ae2-80cf-6ae431403853",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = movielens.drop(columns=['timestamp', 'genres'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b7d779a8-1113-4ee6-8e4d-aa974ac4c28f",
   "metadata": {},
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       "         userId  movieId  rating\n",
       "0             3        1     4.0\n",
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       "\n",
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     "execution_count": 28,
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    "X"
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   "cell_type": "code",
   "execution_count": 25,
   "id": "394a2b0e-79b3-4429-bf9e-4af6612764e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "y = movielens[[\"rating\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b33f88b8-9f6e-448b-8c41-67a51d52b790",
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       "         userId  movieId                                       genres  \\\n",
       "0             3        1  Adventure|Animation|Children|Comedy|Fantasy   \n",
       "1             6        1  Adventure|Animation|Children|Comedy|Fantasy   \n",
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       "9964929  133047   129354                   Comedy|Crime|Drama|Romance   \n",
       "\n",
       "          timestamp  rating  \n",
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     "execution_count": 12,
     "metadata": {},
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   ],
   "source": [
    "movielens"
   ]
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  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "cb573bc0-bb07-4a82-b798-2c47725a1858",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_df, test_df , _, _ = train_test_split(X, y, test_size=0.3, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "41c453c9-e2e4-460e-8fa7-63db1b1f3bab",
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       "      <td>80769</td>\n",
       "      <td>750</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4304572</th>\n",
       "      <td>88858</td>\n",
       "      <td>1513</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6550634</th>\n",
       "      <td>22816</td>\n",
       "      <td>3169</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6423388</th>\n",
       "      <td>8932</td>\n",
       "      <td>3072</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6975451 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         userId  movieId  rating\n",
       "6172755    2539     2916     5.0\n",
       "2259067   86351      778     4.0\n",
       "900381    52088      290     4.5\n",
       "3875514    4951     1277     5.0\n",
       "4925353   81843     1994     4.0\n",
       "...         ...      ...     ...\n",
       "9958614   88342   112623     4.0\n",
       "2234489   80769      750     5.0\n",
       "4304572   88858     1513     4.0\n",
       "6550634   22816     3169     4.0\n",
       "6423388    8932     3072     4.5\n",
       "\n",
       "[6975451 rows x 3 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "92cc7c3c-1fc0-4be0-aaca-1729e94ae351",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_df.to_csv(\"datasets/movielens/train.dat\", index=False, header=False, sep='\\t')\n",
    "test_df.to_csv(\"datasets/movielens/test.dat\", index=False, header=False, sep='\\t')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "b80e343b-88cd-4e33-bcb2-1102dee57ead",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<caserec.recommenders.rating_prediction.svdplusplus.SVDPlusPlus at 0x7f7eb3197970>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SVDPlusPlus(\n",
    "        train_file='datasets/movielens/train.dat',\n",
    "        test_file='datasets/movielens/test.dat',\n",
    "        output_file='datasets/predictions/svdpp_movielens.dat',\n",
    "        epochs=20,\n",
    "        learn_rate=0.005,\n",
    "        delta=0.02,\n",
    "        factors=20,\n",
    "        random_seed=42,\n",
    "        ).compute()"
   ]
  }
 ],
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