code/14.millionsong.ipynb

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   "source": [
    "***\n",
    "***\n",
    "# 使用GraphLab进行音乐推荐\n",
    "***\n",
    "***\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-05T06:07:43.686726Z",
     "start_time": "2018-05-05T06:07:39.415455Z"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[INFO] graphlab.cython.cy_server: GraphLab Create v2.1 started. Logging: /tmp/graphlab_server_1525500461.log\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This non-commercial license of GraphLab Create for academic use is assigned to wangchengjun@nju.edu.cn and will expire on March 14, 2019.\n"
     ]
    }
   ],
   "source": [
    "import graphlab as gl\n",
    "# set canvas to show sframes and sgraphs in ipython notebook\n",
    "gl.canvas.set_target('ipynb')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 下载数据\n",
    "http://s3.amazonaws.com/dato-datasets/millionsong/10000.txt\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-05T06:12:27.320471Z",
     "start_time": "2018-05-05T06:12:24.105760Z"
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     "slide_type": "slide"
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   "outputs": [
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       "    <tr>\n",
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       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">music_id</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">rating</th>\n",
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       "[2000000 rows x 3 columns]<br/>Note: Only the head of the SFrame is printed.<br/>You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.\n",
       "</div>"
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       "Columns:\n",
       "\tuser_id\tstr\n",
       "\tmusic_id\tstr\n",
       "\trating\tint\n",
       "\n",
       "Rows: 2000000\n",
       "\n",
       "Data:\n",
       "+-------------------------------+--------------------+--------+\n",
       "|            user_id            |      music_id      | rating |\n",
       "+-------------------------------+--------------------+--------+\n",
       "| b80344d063b5ccb3212f76538f... | SOAKIMP12A8C130995 |   1    |\n",
       "| b80344d063b5ccb3212f76538f... | SOBBMDR12A8C13253B |   2    |\n",
       "| b80344d063b5ccb3212f76538f... | SOBXHDL12A81C204C0 |   1    |\n",
       "| b80344d063b5ccb3212f76538f... | SOBYHAJ12A6701BF1D |   1    |\n",
       "| b80344d063b5ccb3212f76538f... | SODACBL12A8C13C273 |   1    |\n",
       "| b80344d063b5ccb3212f76538f... | SODDNQT12A6D4F5F7E |   5    |\n",
       "| b80344d063b5ccb3212f76538f... | SODXRTY12AB0180F3B |   1    |\n",
       "| b80344d063b5ccb3212f76538f... | SOFGUAY12AB017B0A8 |   1    |\n",
       "| b80344d063b5ccb3212f76538f... | SOFRQTD12A81C233C0 |   1    |\n",
       "| b80344d063b5ccb3212f76538f... | SOHQWYZ12A6D4FA701 |   1    |\n",
       "+-------------------------------+--------------------+--------+\n",
       "[2000000 rows x 3 columns]\n",
       "Note: Only the head of the SFrame is printed.\n",
       "You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns."
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#train_file = 'http://s3.amazonaws.com/dato-datasets/millionsong/10000.txt'\n",
    "train_file = '/Users/datalab/bigdata/cjc/millionsong/song_usage_10000.txt'\n",
    "sf = gl.SFrame.read_csv(train_file, header=False, delimiter='\\t', verbose=False)\n",
    "sf.rename({'X1':'user_id', 'X2':'music_id', 'X3':'rating'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-05T06:13:05.972248Z",
     "start_time": "2018-05-05T06:13:05.961389Z"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "train_set, test_set = sf.random_split(0.8, seed=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-05T06:13:29.312653Z",
     "start_time": "2018-05-05T06:13:27.066021Z"
    },
    "slideshow": {
     "slide_type": "slide"
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   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>Recsys training: model = popularity</pre>"
      ],
      "text/plain": [
       "Recsys training: model = popularity"
      ]
     },
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    },
    {
     "data": {
      "text/html": [
       "<pre>Preparing data set.</pre>"
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      "text/plain": [
       "Preparing data set."
      ]
     },
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     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>    Data has 1599753 observations with 76085 users and 10000 items.</pre>"
      ],
      "text/plain": [
       "    Data has 1599753 observations with 76085 users and 10000 items."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>    Data prepared in: 1.2441s</pre>"
      ],
      "text/plain": [
       "    Data prepared in: 1.2441s"
      ]
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     "data": {
      "text/html": [
       "<pre>1599753 observations to process; with 10000 unique items.</pre>"
      ],
      "text/plain": [
       "1599753 observations to process; with 10000 unique items."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "popularity_model = gl.popularity_recommender.create(train_set, \n",
    "                                                    'user_id', 'music_id', \n",
    "                                                    target = 'rating')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-05T06:14:56.020548Z",
     "start_time": "2018-05-05T06:14:53.721427Z"
    },
    "slideshow": {
     "slide_type": "slide"
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   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>Recsys training: model = item_similarity</pre>"
      ],
      "text/plain": [
       "Recsys training: model = item_similarity"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>Preparing data set.</pre>"
      ],
      "text/plain": [
       "Preparing data set."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>    Data has 1599753 observations with 76085 users and 10000 items.</pre>"
      ],
      "text/plain": [
       "    Data has 1599753 observations with 76085 users and 10000 items."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>    Data prepared in: 1.18984s</pre>"
      ],
      "text/plain": [
       "    Data prepared in: 1.18984s"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>Training model from provided data.</pre>"
      ],
      "text/plain": [
       "Training model from provided data."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>Gathering per-item and per-user statistics.</pre>"
      ],
      "text/plain": [
       "Gathering per-item and per-user statistics."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------------------------+------------+</pre>"
      ],
      "text/plain": [
       "+--------------------------------+------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| Elapsed Time (Item Statistics) | % Complete |</pre>"
      ],
      "text/plain": [
       "| Elapsed Time (Item Statistics) | % Complete |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------------------------+------------+</pre>"
      ],
      "text/plain": [
       "+--------------------------------+------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 1.549ms                        | 1.25       |</pre>"
      ],
      "text/plain": [
       "| 1.549ms                        | 1.25       |"
      ]
     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre>| 46.313ms                       | 100        |</pre>"
      ],
      "text/plain": [
       "| 46.313ms                       | 100        |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------------------------+------------+</pre>"
      ],
      "text/plain": [
       "+--------------------------------+------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>Setting up lookup tables.</pre>"
      ],
      "text/plain": [
       "Setting up lookup tables."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>Processing data in one pass using dense lookup tables.</pre>"
      ],
      "text/plain": [
       "Processing data in one pass using dense lookup tables."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+-------------------------------------+------------------+-----------------+</pre>"
      ],
      "text/plain": [
       "+-------------------------------------+------------------+-----------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| Elapsed Time (Constructing Lookups) | Total % Complete | Items Processed |</pre>"
      ],
      "text/plain": [
       "| Elapsed Time (Constructing Lookups) | Total % Complete | Items Processed |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+-------------------------------------+------------------+-----------------+</pre>"
      ],
      "text/plain": [
       "+-------------------------------------+------------------+-----------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 264.127ms                           | 0                | 0               |</pre>"
      ],
      "text/plain": [
       "| 264.127ms                           | 0                | 0               |"
      ]
     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre>| 994.743ms                           | 100              | 10000           |</pre>"
      ],
      "text/plain": [
       "| 994.743ms                           | 100              | 10000           |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+-------------------------------------+------------------+-----------------+</pre>"
      ],
      "text/plain": [
       "+-------------------------------------+------------------+-----------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>Finalizing lookup tables.</pre>"
      ],
      "text/plain": [
       "Finalizing lookup tables."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>Generating candidate set for working with new users.</pre>"
      ],
      "text/plain": [
       "Generating candidate set for working with new users."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>Finished training in 1.06117s</pre>"
      ],
      "text/plain": [
       "Finished training in 1.06117s"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "item_sim_model = gl.item_similarity_recommender.create(train_set, \n",
    "                                                       'user_id', 'music_id', \n",
    "                                                       target = 'rating', \n",
    "                                                       similarity_type='cosine')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-05T06:15:27.619180Z",
     "start_time": "2018-05-05T06:15:17.795671Z"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>Recsys training: model = factorization_recommender</pre>"
      ],
      "text/plain": [
       "Recsys training: model = factorization_recommender"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>Preparing data set.</pre>"
      ],
      "text/plain": [
       "Preparing data set."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>    Data has 1599753 observations with 76085 users and 10000 items.</pre>"
      ],
      "text/plain": [
       "    Data has 1599753 observations with 76085 users and 10000 items."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>    Data prepared in: 1.21379s</pre>"
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      "text/plain": [
       "    Data prepared in: 1.21379s"
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     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre>Training factorization_recommender for recommendations.</pre>"
      ],
      "text/plain": [
       "Training factorization_recommender for recommendations."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------------------------+--------------------------------------------------+----------+</pre>"
      ],
      "text/plain": [
       "+--------------------------------+--------------------------------------------------+----------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| Parameter                      | Description                                      | Value    |</pre>"
      ],
      "text/plain": [
       "| Parameter                      | Description                                      | Value    |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------------------------+--------------------------------------------------+----------+</pre>"
      ],
      "text/plain": [
       "+--------------------------------+--------------------------------------------------+----------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| num_factors                    | Factor Dimension                                 | 8        |</pre>"
      ],
      "text/plain": [
       "| num_factors                    | Factor Dimension                                 | 8        |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| regularization                 | L2 Regularization on Factors                     | 1e-08    |</pre>"
      ],
      "text/plain": [
       "| regularization                 | L2 Regularization on Factors                     | 1e-08    |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| solver                         | Solver used for training                         | sgd      |</pre>"
      ],
      "text/plain": [
       "| solver                         | Solver used for training                         | sgd      |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| linear_regularization          | L2 Regularization on Linear Coefficients         | 1e-10    |</pre>"
      ],
      "text/plain": [
       "| linear_regularization          | L2 Regularization on Linear Coefficients         | 1e-10    |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| max_iterations                 | Maximum Number of Iterations                     | 50       |</pre>"
      ],
      "text/plain": [
       "| max_iterations                 | Maximum Number of Iterations                     | 50       |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------------------------+--------------------------------------------------+----------+</pre>"
      ],
      "text/plain": [
       "+--------------------------------+--------------------------------------------------+----------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>  Optimizing model using SGD; tuning step size.</pre>"
      ],
      "text/plain": [
       "  Optimizing model using SGD; tuning step size."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>  Using 199969 / 1599753 points for tuning the step size.</pre>"
      ],
      "text/plain": [
       "  Using 199969 / 1599753 points for tuning the step size."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+---------+-------------------+------------------------------------------+</pre>"
      ],
      "text/plain": [
       "+---------+-------------------+------------------------------------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| Attempt | Initial Step Size | Estimated Objective Value                |</pre>"
      ],
      "text/plain": [
       "| Attempt | Initial Step Size | Estimated Objective Value                |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+---------+-------------------+------------------------------------------+</pre>"
      ],
      "text/plain": [
       "+---------+-------------------+------------------------------------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 0       | 25                | No Decrease (227.564 >= 37.2517)         |</pre>"
      ],
      "text/plain": [
       "| 0       | 25                | No Decrease (227.564 >= 37.2517)         |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 1       | 6.25              | No Decrease (218.774 >= 37.2517)         |</pre>"
      ],
      "text/plain": [
       "| 1       | 6.25              | No Decrease (218.774 >= 37.2517)         |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 2       | 1.5625            | No Decrease (189.223 >= 37.2517)         |</pre>"
      ],
      "text/plain": [
       "| 2       | 1.5625            | No Decrease (189.223 >= 37.2517)         |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 3       | 0.390625          | No Decrease (84.7797 >= 37.2517)         |</pre>"
      ],
      "text/plain": [
       "| 3       | 0.390625          | No Decrease (84.7797 >= 37.2517)         |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 4       | 0.0976562         | 12.0849                                  |</pre>"
      ],
      "text/plain": [
       "| 4       | 0.0976562         | 12.0849                                  |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 5       | 0.0488281         | 8.26182                                  |</pre>"
      ],
      "text/plain": [
       "| 5       | 0.0488281         | 8.26182                                  |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 6       | 0.0244141         | 21.5168                                  |</pre>"
      ],
      "text/plain": [
       "| 6       | 0.0244141         | 21.5168                                  |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+---------+-------------------+------------------------------------------+</pre>"
      ],
      "text/plain": [
       "+---------+-------------------+------------------------------------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| Final   | 0.0488281         | 8.26182                                  |</pre>"
      ],
      "text/plain": [
       "| Final   | 0.0488281         | 8.26182                                  |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+---------+-------------------+------------------------------------------+</pre>"
      ],
      "text/plain": [
       "+---------+-------------------+------------------------------------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>Starting Optimization.</pre>"
      ],
      "text/plain": [
       "Starting Optimization."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+---------+--------------+-------------------+-----------------------+-------------+</pre>"
      ],
      "text/plain": [
       "+---------+--------------+-------------------+-----------------------+-------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| Iter.   | Elapsed Time | Approx. Objective | Approx. Training RMSE | Step Size   |</pre>"
      ],
      "text/plain": [
       "| Iter.   | Elapsed Time | Approx. Objective | Approx. Training RMSE | Step Size   |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+---------+--------------+-------------------+-----------------------+-------------+</pre>"
      ],
      "text/plain": [
       "+---------+--------------+-------------------+-----------------------+-------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| Initial | 72us         | 43.795            | 6.61778               |             |</pre>"
      ],
      "text/plain": [
       "| Initial | 72us         | 43.795            | 6.61778               |             |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+---------+--------------+-------------------+-----------------------+-------------+</pre>"
      ],
      "text/plain": [
       "+---------+--------------+-------------------+-----------------------+-------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 1       | 164.211ms    | 43.5009           | 6.59512               | 0.0488281   |</pre>"
      ],
      "text/plain": [
       "| 1       | 164.211ms    | 43.5009           | 6.59512               | 0.0488281   |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 2       | 310.478ms    | 40.8579           | 6.39166               | 0.0290334   |</pre>"
      ],
      "text/plain": [
       "| 2       | 310.478ms    | 40.8579           | 6.39166               | 0.0290334   |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 3       | 428.164ms    | 37.9236           | 6.15785               | 0.0214205   |</pre>"
      ],
      "text/plain": [
       "| 3       | 428.164ms    | 37.9236           | 6.15785               | 0.0214205   |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 4       | 543.402ms    | 35.1185           | 5.92569               | 0.0172633   |</pre>"
      ],
      "text/plain": [
       "| 4       | 543.402ms    | 35.1185           | 5.92569               | 0.0172633   |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 5       | 661.456ms    | 32.6788           | 5.7161                | 0.014603    |</pre>"
      ],
      "text/plain": [
       "| 5       | 661.456ms    | 32.6788           | 5.7161                | 0.014603    |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 6       | 784.067ms    | 30.599            | 5.53115               | 0.0127367   |</pre>"
      ],
      "text/plain": [
       "| 6       | 784.067ms    | 30.599            | 5.53115               | 0.0127367   |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 10      | 1.25s        | 24.7663           | 4.97592               | 0.008683    |</pre>"
      ],
      "text/plain": [
       "| 10      | 1.25s        | 24.7663           | 4.97592               | 0.008683    |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 11      | 1.38s        | 23.5067           | 4.84768               | 0.00808399  |</pre>"
      ],
      "text/plain": [
       "| 11      | 1.38s        | 23.5067           | 4.84768               | 0.00808399  |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 20      | 2.49s        | 17.6493           | 4.20017               | 0.00516295  |</pre>"
      ],
      "text/plain": [
       "| 20      | 2.49s        | 17.6493           | 4.20017               | 0.00516295  |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 30      | 3.65s        | 14.3453           | 3.78639               | 0.00380916  |</pre>"
      ],
      "text/plain": [
       "| 30      | 3.65s        | 14.3453           | 3.78639               | 0.00380916  |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 40      | 4.88s        | 12.6728           | 3.55862               | 0.00306991  |</pre>"
      ],
      "text/plain": [
       "| 40      | 4.88s        | 12.6728           | 3.55862               | 0.00306991  |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 50      | 6.13s        | 11.2253           | 3.34901               | 0.00218366  |</pre>"
      ],
      "text/plain": [
       "| 50      | 6.13s        | 11.2253           | 3.34901               | 0.00218366  |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+---------+--------------+-------------------+-----------------------+-------------+</pre>"
      ],
      "text/plain": [
       "+---------+--------------+-------------------+-----------------------+-------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>Optimization Complete: Maximum number of passes through the data reached.</pre>"
      ],
      "text/plain": [
       "Optimization Complete: Maximum number of passes through the data reached."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>Computing final objective value and training RMSE.</pre>"
      ],
      "text/plain": [
       "Computing final objective value and training RMSE."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>       Final objective value: 9.81513</pre>"
      ],
      "text/plain": [
       "       Final objective value: 9.81513"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>       Final training RMSE: 3.1314</pre>"
      ],
      "text/plain": [
       "       Final training RMSE: 3.1314"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "factorization_machine_model = gl.recommender.factorization_recommender.create(train_set, \n",
    "                                                                              'user_id', 'music_id',\n",
    "                                                                              target='rating')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-05T06:23:07.088596Z",
     "start_time": "2018-05-05T06:23:07.080111Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1599753"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(train_set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-05T06:22:12.197893Z",
     "start_time": "2018-05-05T06:21:47.643985Z"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "compare_models: using 34355 users to estimate model performance\n",
      "PROGRESS: Evaluate model M0\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 1000/34355 queries. users per second: 18058.4</pre>"
      ],
      "text/plain": [
       "recommendations finished on 1000/34355 queries. users per second: 18058.4"
      ]
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     "metadata": {},
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    },
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     "data": {
      "text/html": [
       "<pre>recommendations finished on 2000/34355 queries. users per second: 21323.8</pre>"
      ],
      "text/plain": [
       "recommendations finished on 2000/34355 queries. users per second: 21323.8"
      ]
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     "metadata": {},
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    },
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     "data": {
      "text/html": [
       "<pre>recommendations finished on 3000/34355 queries. users per second: 22068.6</pre>"
      ],
      "text/plain": [
       "recommendations finished on 3000/34355 queries. users per second: 22068.6"
      ]
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     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 4000/34355 queries. users per second: 22236.7</pre>"
      ],
      "text/plain": [
       "recommendations finished on 4000/34355 queries. users per second: 22236.7"
      ]
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     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 5000/34355 queries. users per second: 22389.4</pre>"
      ],
      "text/plain": [
       "recommendations finished on 5000/34355 queries. users per second: 22389.4"
      ]
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     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 6000/34355 queries. users per second: 22147</pre>"
      ],
      "text/plain": [
       "recommendations finished on 6000/34355 queries. users per second: 22147"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 7000/34355 queries. users per second: 22349.2</pre>"
      ],
      "text/plain": [
       "recommendations finished on 7000/34355 queries. users per second: 22349.2"
      ]
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     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 8000/34355 queries. users per second: 22358.7</pre>"
      ],
      "text/plain": [
       "recommendations finished on 8000/34355 queries. users per second: 22358.7"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 9000/34355 queries. users per second: 22426.9</pre>"
      ],
      "text/plain": [
       "recommendations finished on 9000/34355 queries. users per second: 22426.9"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 10000/34355 queries. users per second: 22486.8</pre>"
      ],
      "text/plain": [
       "recommendations finished on 10000/34355 queries. users per second: 22486.8"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 11000/34355 queries. users per second: 22207.4</pre>"
      ],
      "text/plain": [
       "recommendations finished on 11000/34355 queries. users per second: 22207.4"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 12000/34355 queries. users per second: 22163.2</pre>"
      ],
      "text/plain": [
       "recommendations finished on 12000/34355 queries. users per second: 22163.2"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 13000/34355 queries. users per second: 22060.5</pre>"
      ],
      "text/plain": [
       "recommendations finished on 13000/34355 queries. users per second: 22060.5"
      ]
     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 14000/34355 queries. users per second: 22038</pre>"
      ],
      "text/plain": [
       "recommendations finished on 14000/34355 queries. users per second: 22038"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 15000/34355 queries. users per second: 22088.7</pre>"
      ],
      "text/plain": [
       "recommendations finished on 15000/34355 queries. users per second: 22088.7"
      ]
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     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 16000/34355 queries. users per second: 22082.8</pre>"
      ],
      "text/plain": [
       "recommendations finished on 16000/34355 queries. users per second: 22082.8"
      ]
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     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 17000/34355 queries. users per second: 22162.7</pre>"
      ],
      "text/plain": [
       "recommendations finished on 17000/34355 queries. users per second: 22162.7"
      ]
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     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 18000/34355 queries. users per second: 22229.9</pre>"
      ],
      "text/plain": [
       "recommendations finished on 18000/34355 queries. users per second: 22229.9"
      ]
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     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 19000/34355 queries. users per second: 22293.3</pre>"
      ],
      "text/plain": [
       "recommendations finished on 19000/34355 queries. users per second: 22293.3"
      ]
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     "metadata": {},
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    {
     "data": {
      "text/html": [
       "<pre>recommendations finished on 20000/34355 queries. users per second: 22182.1</pre>"
      ],
      "text/plain": [
       "recommendations finished on 20000/34355 queries. users per second: 22182.1"
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     "metadata": {},
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     "data": {
      "text/html": [
       "<pre>recommendations finished on 21000/34355 queries. users per second: 22132.2</pre>"
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      "text/plain": [
       "recommendations finished on 21000/34355 queries. users per second: 22132.2"
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     "metadata": {},
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     "data": {
      "text/html": [
       "<pre>recommendations finished on 22000/34355 queries. users per second: 22136.5</pre>"
      ],
      "text/plain": [
       "recommendations finished on 22000/34355 queries. users per second: 22136.5"
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     "data": {
      "text/html": [
       "<pre>recommendations finished on 23000/34355 queries. users per second: 21993.7</pre>"
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     "data": {
      "text/html": [
       "<pre>recommendations finished on 24000/34355 queries. users per second: 21916.9</pre>"
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      "\n",
      "Precision and recall summary statistics by cutoff\n",
      "+--------+-------------------+-------------------+\n",
      "| cutoff |   mean_precision  |    mean_recall    |\n",
      "+--------+-------------------+-------------------+\n",
      "|   1    | 0.000320186290205 | 2.62069953527e-05 |\n",
      "|   2    | 0.000363848057051 | 0.000157978795732 |\n",
      "|   3    | 0.000368699364479 | 0.000246448831037 |\n",
      "|   4    | 0.000451171590744 |  0.00045461967667 |\n",
      "|   5    | 0.000518119633241 | 0.000646663196468 |\n",
      "|   6    | 0.000499684665017 | 0.000719981467646 |\n",
      "|   7    | 0.000478200303553 | 0.000800163591435 |\n",
      "|   8    | 0.000451171590744 | 0.000835628106468 |\n",
      "|   9    | 0.000501301767493 | 0.000996939435667 |\n",
      "|   10   | 0.000474457866395 |  0.00104312051081 |\n",
      "+--------+-------------------+-------------------+\n",
      "[10 rows x 3 columns]\n",
      "\n",
      "('\\nOverall RMSE: ', 6.470445808584627)\n",
      "\n",
      "Per User RMSE (best)\n",
      "+-------------------------------+-------+------+\n",
      "|            user_id            | count | rmse |\n",
      "+-------------------------------+-------+------+\n",
      "| 6d61c9b3678aa6c015ea9fd502... |   1   | 0.0  |\n",
      "+-------------------------------+-------+------+\n",
      "[1 rows x 3 columns]\n",
      "\n",
      "\n",
      "Per User RMSE (worst)\n",
      "+-------------------------------+-------+---------------+\n",
      "|            user_id            | count |      rmse     |\n",
      "+-------------------------------+-------+---------------+\n",
      "| 50996bbabb6f7857bf0c801943... |   2   | 647.013311924 |\n",
      "+-------------------------------+-------+---------------+\n",
      "[1 rows x 3 columns]\n",
      "\n",
      "\n",
      "Per Item RMSE (best)\n",
      "+--------------------+-------+-----------------+\n",
      "|      music_id      | count |       rmse      |\n",
      "+--------------------+-------+-----------------+\n",
      "| SOXDPFW12A81C2319B |   8   | 0.0735294117647 |\n",
      "+--------------------+-------+-----------------+\n",
      "[1 rows x 3 columns]\n",
      "\n",
      "\n",
      "Per Item RMSE (worst)\n",
      "+--------------------+-------+---------------+\n",
      "|      music_id      | count |      rmse     |\n",
      "+--------------------+-------+---------------+\n",
      "| SOUAGPQ12A8AE47B3A |   8   | 323.517367637 |\n",
      "+--------------------+-------+---------------+\n",
      "[1 rows x 3 columns]\n",
      "\n",
      "PROGRESS: Evaluate model M1\n"
     ]
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      "\n",
      "Precision and recall summary statistics by cutoff\n",
      "+--------+-----------------+-----------------+\n",
      "| cutoff |  mean_precision |   mean_recall   |\n",
      "+--------+-----------------+-----------------+\n",
      "|   1    | 0.0505894338524 | 0.0151970338993 |\n",
      "|   2    | 0.0616795226313 | 0.0336650217808 |\n",
      "|   3    | 0.0729927715519 | 0.0543725425713 |\n",
      "|   4    | 0.0751055159365 | 0.0704135431553 |\n",
      "|   5    | 0.0741726095183 | 0.0842718589105 |\n",
      "|   6    | 0.0725076408092 | 0.0963338861128 |\n",
      "|   7    | 0.0700792149198 |  0.106287905834 |\n",
      "|   8    | 0.0680978023577 |  0.115967909942 |\n",
      "|   9    |   0.0657740261  |  0.124363659149 |\n",
      "|   10   | 0.0636239266482 |  0.13230804769  |\n",
      "+--------+-----------------+-----------------+\n",
      "[10 rows x 3 columns]\n",
      "\n",
      "('\\nOverall RMSE: ', 7.150718576843326)\n",
      "\n",
      "Per User RMSE (best)\n",
      "+-------------------------------+-------+-------------------+\n",
      "|            user_id            | count |        rmse       |\n",
      "+-------------------------------+-------+-------------------+\n",
      "| dad5cd4678a6f6df34932432bc... |   1   | 0.000917145184108 |\n",
      "+-------------------------------+-------+-------------------+\n",
      "[1 rows x 3 columns]\n",
      "\n",
      "\n",
      "Per User RMSE (worst)\n",
      "+-------------------------------+-------+---------------+\n",
      "|            user_id            | count |      rmse     |\n",
      "+-------------------------------+-------+---------------+\n",
      "| 50996bbabb6f7857bf0c801943... |   2   | 650.121367005 |\n",
      "+-------------------------------+-------+---------------+\n",
      "[1 rows x 3 columns]\n",
      "\n",
      "\n",
      "Per Item RMSE (best)\n",
      "+--------------------+-------+---------------+\n",
      "|      music_id      | count |      rmse     |\n",
      "+--------------------+-------+---------------+\n",
      "| SOJUKCL12A6D4F7DF7 |   3   | 0.75550628309 |\n",
      "+--------------------+-------+---------------+\n",
      "[1 rows x 3 columns]\n",
      "\n",
      "\n",
      "Per Item RMSE (worst)\n",
      "+--------------------+-------+---------------+\n",
      "|      music_id      | count |      rmse     |\n",
      "+--------------------+-------+---------------+\n",
      "| SOUAGPQ12A8AE47B3A |   8   | 325.077941681 |\n",
      "+--------------------+-------+---------------+\n",
      "[1 rows x 3 columns]\n",
      "\n",
      "PROGRESS: Evaluate model M2\n"
     ]
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Precision and recall summary statistics by cutoff\n",
      "+--------+-------------------+-------------------+\n",
      "| cutoff |   mean_precision  |    mean_recall    |\n",
      "+--------+-------------------+-------------------+\n",
      "|   1    | 0.000436617668462 | 8.84193897883e-05 |\n",
      "|   2    | 0.000392955901615 | 0.000146983613211 |\n",
      "|   3    | 0.000397807209043 | 0.000273528343889 |\n",
      "|   4    | 0.000400232862757 | 0.000328267207427 |\n",
      "|   5    | 0.000424974530636 |  0.00040585165237 |\n",
      "|   6    | 0.000460874205598 | 0.000574532683748 |\n",
      "|   7    |  0.00049483335759 | 0.000721448772082 |\n",
      "|   8    | 0.000531218163295 | 0.000887467388127 |\n",
      "|   9    |  0.00055628325167 |  0.00109888572439 |\n",
      "|   10   | 0.000593800029108 |  0.00130662212516 |\n",
      "+--------+-------------------+-------------------+\n",
      "[10 rows x 3 columns]\n",
      "\n",
      "('\\nOverall RMSE: ', 8.111262615677196)\n",
      "\n",
      "Per User RMSE (best)\n",
      "+-------------------------------+-------+-------------------+\n",
      "|            user_id            | count |        rmse       |\n",
      "+-------------------------------+-------+-------------------+\n",
      "| 06aad545e9390a6332a7fee7f3... |   1   | 0.000536064571246 |\n",
      "+-------------------------------+-------+-------------------+\n",
      "[1 rows x 3 columns]\n",
      "\n",
      "\n",
      "Per User RMSE (worst)\n",
      "+-------------------------------+-------+---------------+\n",
      "|            user_id            | count |      rmse     |\n",
      "+-------------------------------+-------+---------------+\n",
      "| 50996bbabb6f7857bf0c801943... |   2   | 689.967975368 |\n",
      "+-------------------------------+-------+---------------+\n",
      "[1 rows x 3 columns]\n",
      "\n",
      "\n",
      "Per Item RMSE (best)\n",
      "+--------------------+-------+-----------------+\n",
      "|      music_id      | count |       rmse      |\n",
      "+--------------------+-------+-----------------+\n",
      "| SOJWSGL12A81C217B0 |   2   | 0.0503145302263 |\n",
      "+--------------------+-------+-----------------+\n",
      "[1 rows x 3 columns]\n",
      "\n",
      "\n",
      "Per Item RMSE (worst)\n",
      "+--------------------+-------+---------------+\n",
      "|      music_id      | count |      rmse     |\n",
      "+--------------------+-------+---------------+\n",
      "| SOUAGPQ12A8AE47B3A |   8   | 345.207580713 |\n",
      "+--------------------+-------+---------------+\n",
      "[1 rows x 3 columns]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "result = gl.recommender.util.compare_models(test_set, \n",
    "                                            [popularity_model, item_sim_model, factorization_machine_model],\n",
    "                                            user_sample=.5, skip_set=train_set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-05T06:09:56.940553Z",
     "start_time": "2018-05-05T06:09:56.453602Z"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "K = 10\n",
    "users = gl.SArray(sf['user_id'].unique().head(100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-05T06:09:57.774575Z",
     "start_time": "2018-05-05T06:09:57.694466Z"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">user_id</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">music_id</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">score</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">rank</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">279292bb36dbfc7f505e36ebf<br>038c81eb1d1d63e ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">SOXUQNR12AF72A69D6</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3.02242265145</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">279292bb36dbfc7f505e36ebf<br>038c81eb1d1d63e ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">SOUFAZA12AC3DFAB20</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1.33684277534</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">279292bb36dbfc7f505e36ebf<br>038c81eb1d1d63e ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">SOSFSTC12A8C141219</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1.09198212624</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">279292bb36dbfc7f505e36ebf<br>038c81eb1d1d63e ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">SOVIWFP12A58A7D1BD</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1.04516386986</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">279292bb36dbfc7f505e36ebf<br>038c81eb1d1d63e ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">SOBMTQD12AB01833D0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1.02945168813</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">279292bb36dbfc7f505e36ebf<br>038c81eb1d1d63e ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">SOCMNRG12AB0189D3F</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.975643793742</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">279292bb36dbfc7f505e36ebf<br>038c81eb1d1d63e ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">SOXOHUM12A67ADC826</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.950687328974</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">279292bb36dbfc7f505e36ebf<br>038c81eb1d1d63e ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">SOWBFVW12A6D4F612B</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.909237066905</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">279292bb36dbfc7f505e36ebf<br>038c81eb1d1d63e ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">SOXFYTY127E9433E7D</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.897727807363</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">279292bb36dbfc7f505e36ebf<br>038c81eb1d1d63e ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">SOYBLYP12A58A79D32</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.897092819214</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[10 rows x 4 columns]<br/>\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tuser_id\tstr\n",
       "\tmusic_id\tstr\n",
       "\tscore\tfloat\n",
       "\trank\tint\n",
       "\n",
       "Rows: 10\n",
       "\n",
       "Data:\n",
       "+-------------------------------+--------------------+----------------+------+\n",
       "|            user_id            |      music_id      |     score      | rank |\n",
       "+-------------------------------+--------------------+----------------+------+\n",
       "| 279292bb36dbfc7f505e36ebf0... | SOXUQNR12AF72A69D6 | 3.02242265145  |  1   |\n",
       "| 279292bb36dbfc7f505e36ebf0... | SOUFAZA12AC3DFAB20 | 1.33684277534  |  2   |\n",
       "| 279292bb36dbfc7f505e36ebf0... | SOSFSTC12A8C141219 | 1.09198212624  |  3   |\n",
       "| 279292bb36dbfc7f505e36ebf0... | SOVIWFP12A58A7D1BD | 1.04516386986  |  4   |\n",
       "| 279292bb36dbfc7f505e36ebf0... | SOBMTQD12AB01833D0 | 1.02945168813  |  5   |\n",
       "| 279292bb36dbfc7f505e36ebf0... | SOCMNRG12AB0189D3F | 0.975643793742 |  6   |\n",
       "| 279292bb36dbfc7f505e36ebf0... | SOXOHUM12A67ADC826 | 0.950687328974 |  7   |\n",
       "| 279292bb36dbfc7f505e36ebf0... | SOWBFVW12A6D4F612B | 0.909237066905 |  8   |\n",
       "| 279292bb36dbfc7f505e36ebf0... | SOXFYTY127E9433E7D | 0.897727807363 |  9   |\n",
       "| 279292bb36dbfc7f505e36ebf0... | SOYBLYP12A58A79D32 | 0.897092819214 |  10  |\n",
       "+-------------------------------+--------------------+----------------+------+\n",
       "[10 rows x 4 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recs = item_sim_model.recommend(users=users, k=K)\n",
    "recs.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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