{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Week 5: Recommending songs" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this module, we focused on building recommender systems to find products, music and movies that interest users. We also built an exciting iPython notebook for recommending songs, which compared the simple popularity-based recommendation with a personalized model, and showed the significant improvement provided by personalization.\n", "\n", "In this assignment, we are going to explore the song data and the recommendations made by our model. In the process, you are going to learn how to use one of the most important data manipulation primitives, groupby. These techniques will be important to building the intelligent application in your capstone project." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Learning outcomes\n", "\n", "- Execute song recommendation code with the iPython notebook\n", "- Load and transform real, song data\n", "- Build a song recommender model\n", "- Use the model to recommend songs to individual users\n", "- Use groupby to compute aggregate statistics of the data" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[INFO] This non-commercial license of GraphLab Create is assigned to chengjun@chem.ku.dk and will expire on January 27, 2017. For commercial licensing options, visit https://dato.com/buy/.\n", "\n", "[INFO] Start server at: ipc:///tmp/graphlab_server-26409 - Server binary: /usr/local/lib/python2.7/site-packages/graphlab/unity_server - Server log: /tmp/graphlab_server_1454571377.log\n", "[INFO] GraphLab Server Version: 1.8.1\n", "[WARNING] Unable to create session in specified location: '/Users/jcj/.graphlab/artifacts'. Using: '/var/tmp/graphlab-jcj/26409/tmp_session_665bc019-a9fc-44cd-9f14-3f24dee4d997'\n" ] } ], "source": [ "import graphlab " ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "graphlab.canvas.set_target('ipynb')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Load and explore the data" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "song_data = graphlab.SFrame('song_data.gl/')" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "data": { "application/javascript": [ "$(\"head\").append($(\"\").attr({\n", " rel: \"stylesheet\",\n", " type: \"text/css\",\n", " href: \"//cdnjs.cloudflare.com/ajax/libs/font-awesome/4.1.0/css/font-awesome.min.css\"\n", "}));\n", "$(\"head\").append($(\"\").attr({\n", " rel: \"stylesheet\",\n", " type: \"text/css\",\n", " href: \"//dato.com/files/canvas/1.8.1/css/canvas.css\"\n", "}));\n", "\n", " (function(){\n", "\n", " var e = null;\n", " if (typeof element == 'undefined') {\n", " var scripts = document.getElementsByTagName('script');\n", " var thisScriptTag = scripts[scripts.length-1];\n", " var parentDiv = thisScriptTag.parentNode;\n", " e = document.createElement('div');\n", " parentDiv.appendChild(e);\n", " } else {\n", " e = element[0];\n", " }\n", "\n", " if (typeof requirejs !== 'undefined') {\n", " // disable load timeout; ipython_app.js is large and can take a while to load.\n", " requirejs.config({waitSeconds: 0});\n", " }\n", "\n", " require(['//dato.com/files/canvas/1.8.1/js/ipython_app.js'], function(IPythonApp){\n", " var app = new IPythonApp();\n", " app.attachView('sarray','Categorical', {\"ipython\": true, \"sketch\": {\"complete\": true, \"numeric\": false, \"num_unique\": 9915, \"num_undefined\": 0, \"progress\": 1.0, \"frequent_items\": {\"Mountain Song ( LP Version ) - Jane's Addiction\": {\"frequency\": 70, \"value\": \"Mountain Song ( LP ...\"}, \"Expectations - Belle and Sebastian\": {\"frequency\": 97, \"value\": \"Expectations - ...\"}, \"Intro - Jay-Z\": {\"frequency\": 62, \"value\": \"Intro - Jay-Z\"}, \"Don't Be Shy - Cat Stevens\": {\"frequency\": 69, \"value\": \"Don't Be Shy - Cat ...\"}, \"Heavyweight - Infected Mushroom\": {\"frequency\": 50, \"value\": \"Heavyweight - ...\"}, \"I Could Fall In Love - Selena\": {\"frequency\": 66, \"value\": \"I Could Fall In ...\"}, \"My Baby Left Me - Creedence Clearwater Revival\": {\"frequency\": 52, \"value\": \"My Baby Left Me - ...\"}, \"I'm Still A Guy - Brad Paisley\": {\"frequency\": 96, \"value\": \"I'm Still A Guy - ...\"}, \"Rock Star - N.E.R.D.\": {\"frequency\": 1189, \"value\": \"Rock Star - ...\"}, \"Ribbons - Four Tet\": {\"frequency\": 24, \"value\": \"Ribbons - Four Tet\"}, \"Everything - Kaskade\": {\"frequency\": 49, \"value\": \"Everything - ...\"}, \"Some Unholy War - Amy Winehouse\": {\"frequency\": 129, \"value\": \"Some Unholy War - ...\"}, \"Kiss With A Fist - Florence + The Machine\": {\"frequency\": 729, \"value\": \"Kiss With A Fist - ...\"}, \"B\\ufffd\\ufffdrang\\ufffd\\ufffdre's Nightmare - Herbie Hancock\": {\"frequency\": 70, \"value\": \"B\\u00e9rang\\u00e8re's ...\"}, \"Tighten Up - The Black Keys\": {\"frequency\": 982, \"value\": \"Tighten Up - The ...\"}, \"Sehnsucht - Rammstein\": {\"frequency\": 160, \"value\": \"Sehnsucht - ...\"}, \"Parallel Universe (Album Version) - Red Hot Chili Peppers\": {\"frequency\": 45, \"value\": \"Parallel Universe ...\"}, \"My Last Song To Jenny - The Avett Brothers\": {\"frequency\": 67, \"value\": \"My Last Song To ...\"}, \"He's A Pirate - Klaus Badelt\": {\"frequency\": 135, \"value\": \"He's A Pirate - ...\"}, \"Every Little Thing She Does Is Magic - The Police\": {\"frequency\": 366, \"value\": \"Every Little Thing ...\"}, \"The Mess I Made - Parachute\": {\"frequency\": 62, \"value\": \"The Mess I Made - ...\"}, \"Too Much (LP Version) - Pepper\": {\"frequency\": 41, \"value\": \"Too Much (LP ...\"}, \"Miss Your Touch (Album Version) - Cassie\": {\"frequency\": 93, \"value\": \"Miss Your Touch ...\"}, \"Ghosts 'n' Stuff (Original Instrumental Mix) - Deadmau5\": {\"frequency\": 814, \"value\": \"Ghosts 'n' Stuff ...\"}, \"Opening Up (Ce Soir On Danse) - Chromeo\": {\"frequency\": 55, \"value\": \"Opening Up (Ce ...\"}, \"Three Cheers For Five Years - Mayday Parade\": {\"frequency\": 89, \"value\": \"Three Cheers For ...\"}, \"Work (Explicit) - Gang Starr\": {\"frequency\": 86, \"value\": \"Work (Explicit) - ...\"}, \"Tacobel Canon - Ratatat\": {\"frequency\": 41, \"value\": \"Tacobel Canon - ...\"}, \"Me Demoro (vivo) - Joe Vasconcellos\": {\"frequency\": 50, \"value\": \"Me Demoro (vivo) - ...\"}, \"La Valse Des Monstres (Live) - Yann Tiersen\": {\"frequency\": 50, \"value\": \"La Valse Des ...\"}, \"Fear - OneRepublic\": {\"frequency\": 64, \"value\": \"Fear - OneRepublic\"}, \"Bag Lady - Erykah Badu\": {\"frequency\": 58, \"value\": \"Bag Lady - Erykah ...\"}, \"Rewind [feat. 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Kanye West) (Rusko Remix) - Kid Sister\": {\"frequency\": 85, \"value\": \"Pro Nails (feat. ...\"}, \"Godspeed - Anberlin\": {\"frequency\": 59, \"value\": \"Godspeed - ...\"}, \"Bonafied Lovin (Radio Edit) - Chromeo\": {\"frequency\": 130, \"value\": \"Bonafied Lovin ...\"}, \"Television Rules The Nation - Daft Punk\": {\"frequency\": 71, \"value\": \"Television Rules ...\"}, \"Lost In Love - Air Supply\": {\"frequency\": 50, \"value\": \"Lost In Love - Air ...\"}, \"Unrecorded - M83\": {\"frequency\": 33, \"value\": \"Unrecorded - M83\"}, \"Slow Moves - Jos\\ufffd\\ufffd Gonz\\ufffd\\ufffdlez\": {\"frequency\": 42, \"value\": \"Slow Moves - Jos\\u00e9 ...\"}, \"Let's Dance (Remastered Album Version ) - Ramones\": {\"frequency\": 37, \"value\": \"Let's Dance ...\"}}, \"size\": 1116609}, \"selected_variable\": {\"name\": [\"\"], \"dtype\": \"str\", \"view_component\": \"Categorical\", \"view_file\": \"sarray\", \"descriptives\": {\"rows\": 1116609}, \"type\": \"SArray\", \"view_components\": [\"Categorical\"]}, \"histogram\": null}, e);\n", " });\n", " })();\n", " " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "song_data['song'].show()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "1116609" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(song_data)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [], "source": [ "users = song_data['user_id'].unique()" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "66346" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(users)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Create a song recommender" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": true }, "outputs": [], "source": [ "train_data, test_data = song_data.random_split(.8, seed=0)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "PROGRESS: Recsys training: model = popularity\n", "PROGRESS: Warning: Ignoring columns song_id, listen_count, title, artist;\n", "PROGRESS: To use one of these as a target column, set target = \n", "PROGRESS: and use a method that allows the use of a target.\n", "PROGRESS: Preparing data set.\n", "PROGRESS: Data has 893580 observations with 66085 users and 9952 items.\n", "PROGRESS: Data prepared in: 1.13117s\n", "PROGRESS: 893580 observations to process; with 9952 unique items.\n" ] } ], "source": [ "popularity_model = graphlab.popularity_recommender.create(train_data,\n", " user_id='user_id',\n", " item_id='song')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Use the popularity model to make some predictions\n", "\n", "A popularity model makes the same prediction for all users, so provides no personalization." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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user_idsongscorerank
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fd5063e5cd9dfe8 ...		Undo - Björk4227.02
c66c10a9567f0d82ff31441a9
fd5063e5cd9dfe8 ...		You're The One - Dwight
Yoakam ...		3781.03
c66c10a9567f0d82ff31441a9
fd5063e5cd9dfe8 ...		Dog Days Are Over (Radio
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fd5063e5cd9dfe8 ...		Revelry - Kings Of Leon3527.05
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fd5063e5cd9dfe8 ...		Horn Concerto No. 4 in E
flat K495: II. Romance ...		3161.06
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fd5063e5cd9dfe8 ...		Secrets - OneRepublic3148.07
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fd5063e5cd9dfe8 ...		Fireflies - Charttraxx
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c66c10a9567f0d82ff31441a9
fd5063e5cd9dfe8 ...		Tive Sim - Cartola2521.09
c66c10a9567f0d82ff31441a9
fd5063e5cd9dfe8 ...		Drop The World - Lil
Wayne / Eminem ...		2053.010
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" ], "text/plain": [ "Columns:\n", "\tuser_id\tstr\n", "\tsong\tstr\n", "\tscore\tfloat\n", "\trank\tint\n", "\n", "Rows: 10\n", "\n", "Data:\n", "+-------------------------------+--------------------------------+--------+------+\n", "| user_id | song | score | rank |\n", "+-------------------------------+--------------------------------+--------+------+\n", "| c66c10a9567f0d82ff31441a9f... | Sehr kosmisch - Harmonia | 4754.0 | 1 |\n", "| c66c10a9567f0d82ff31441a9f... | Undo - Björk | 4227.0 | 2 |\n", "| c66c10a9567f0d82ff31441a9f... | You're The One - Dwight Yoakam | 3781.0 | 3 |\n", "| c66c10a9567f0d82ff31441a9f... | Dog Days Are Over (Radio E... | 3633.0 | 4 |\n", "| c66c10a9567f0d82ff31441a9f... | Revelry - Kings Of Leon | 3527.0 | 5 |\n", "| c66c10a9567f0d82ff31441a9f... | Horn Concerto No. 4 in E f... | 3161.0 | 6 |\n", "| c66c10a9567f0d82ff31441a9f... | Secrets - OneRepublic | 3148.0 | 7 |\n", "| c66c10a9567f0d82ff31441a9f... | Fireflies - Charttraxx Karaoke | 2532.0 | 8 |\n", "| c66c10a9567f0d82ff31441a9f... | Tive Sim - Cartola | 2521.0 | 9 |\n", "| c66c10a9567f0d82ff31441a9f... | Drop The World - Lil Wayne... | 2053.0 | 10 |\n", "+-------------------------------+--------------------------------+--------+------+\n", "[10 rows x 4 columns]" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "popularity_model.recommend(users=[users[0]])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Build a song recommender with personalization\n", "\n", "We now create a model that allows us to make personalized recommendations to each user." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "PROGRESS: Recsys training: model = item_similarity\n", "PROGRESS: Warning: Ignoring columns song_id, listen_count, title, artist;\n", "PROGRESS: To use one of these as a target column, set target = \n", "PROGRESS: and use a method that allows the use of a target.\n", "PROGRESS: Preparing data set.\n", "PROGRESS: Data has 893580 observations with 66085 users and 9952 items.\n", "PROGRESS: Data prepared in: 1.4713s\n", "PROGRESS: Computing item similarity statistics:\n", "PROGRESS: Computing most similar items for 9952 items:\n", "PROGRESS: +-----------------+-----------------+\n", "PROGRESS: | Number of items | Elapsed Time |\n", "PROGRESS: +-----------------+-----------------+\n", "PROGRESS: | 1000 | 1.75823 |\n", "PROGRESS: | 2000 | 1.82732 |\n", "PROGRESS: | 3000 | 1.89268 |\n", "PROGRESS: | 4000 | 1.95487 |\n", "PROGRESS: | 5000 | 2.01536 |\n", "PROGRESS: | 6000 | 2.07326 |\n", "PROGRESS: | 7000 | 2.13279 |\n", "PROGRESS: | 8000 | 2.2052 |\n", "PROGRESS: | 9000 | 2.28086 |\n", "PROGRESS: +-----------------+-----------------+\n", "PROGRESS: Finished training in 2.75342s\n" ] } ], "source": [ "personalized_model = graphlab.item_similarity_recommender.create(train_data,\n", " user_id='user_id',\n", " item_id='song')" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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user_idsongscorerank
c66c10a9567f0d82ff31441a9
fd5063e5cd9dfe8 ...		Cuando Pase El Temblor -
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fd5063e5cd9dfe8 ...		Secrets - OneRepublic0.01361026760355
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fd5063e5cd9dfe8 ...		Y solo se me ocurre
amarte (Unplugged) - ...		0.01332103853698
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fd5063e5cd9dfe8 ...		Te Hacen Falta Vitaminas
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fd5063e5cd9dfe8 ...		OMG - Usher featuring
will.i.am ...		0.01278321194610
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user_idsongscorerank
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Nine - Dr Feelgood ...		0.03751
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038c81eb1d1d63e ...		Sei Lá Mangueira -
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038c81eb1d1d63e ...		Audience Of One - Rise
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038c81eb1d1d63e ...		Blame It On The Boogie -
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songsimilarscorerank
With Or Without You - U2I Still Haven't Found
What I'm Looking For ...		0.04285714285711
With Or Without You - U2Hold Me_ Thrill Me_ Kiss
Me_ Kill Me - U2 ...		0.0337349397592
With Or Without You - U2Window In The Skies - U20.03283582089553
With Or Without You - U2Vertigo - U20.03007518796994
With Or Without You - U2Sunday Bloody Sunday - U20.02713178294575
With Or Without You - U2Bad - U20.02517985611516
With Or Without You - U2A Day Without Me - U20.02371541501987
With Or Without You - U2Another Time Another
Place - U2 ...		0.0203252032528
With Or Without You - U2Walk On - U20.0202020202029
With Or Without You - U2Get On Your Boots - U20.019685039370110
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" ], "text/plain": [ "Columns:\n", "\tsong\tstr\n", "\tsimilar\tstr\n", "\tscore\tfloat\n", "\trank\tint\n", "\n", "Rows: 10\n", "\n", "Data:\n", "+--------------------------+-------------------------------+-----------------+\n", "| song | similar | score |\n", "+--------------------------+-------------------------------+-----------------+\n", "| With Or Without You - U2 | I Still Haven't Found What... | 0.0428571428571 |\n", "| With Or Without You - U2 | Hold Me_ Thrill Me_ Kiss M... | 0.033734939759 |\n", "| With Or Without You - U2 | Window In The Skies - U2 | 0.0328358208955 |\n", "| With Or Without You - U2 | Vertigo - U2 | 0.0300751879699 |\n", "| With Or Without You - U2 | Sunday Bloody Sunday - U2 | 0.0271317829457 |\n", "| With Or Without You - U2 | Bad - U2 | 0.0251798561151 |\n", "| With Or Without You - U2 | A Day Without Me - U2 | 0.0237154150198 |\n", "| With Or Without You - U2 | Another Time Another Place... | 0.020325203252 |\n", "| With Or Without You - U2 | Walk On - U2 | 0.020202020202 |\n", "| With Or Without You - U2 | Get On Your Boots - U2 | 0.0196850393701 |\n", "+--------------------------+-------------------------------+-----------------+\n", "+------+\n", "| rank |\n", "+------+\n", "| 1 |\n", "| 2 |\n", "| 3 |\n", "| 4 |\n", "| 5 |\n", "| 6 |\n", "| 7 |\n", "| 8 |\n", "| 9 |\n", "| 10 |\n", "+------+\n", "[10 rows x 4 columns]" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "personalized_model.get_similar_items(['With Or Without You - U2'])" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": true }, "outputs": [], "source": [ "#%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "compare_models: using 2931 users to estimate model performance\n", "PROGRESS: Evaluate model M0\n", "PROGRESS: recommendations finished on 1000/2931 queries. users per second: 9913.55\n", "PROGRESS: recommendations finished on 2000/2931 queries. users per second: 12771\n", "\n", "Precision and recall summary statistics by cutoff\n", "+--------+-----------------+------------------+\n", "| cutoff | mean_precision | mean_recall |\n", "+--------+-----------------+------------------+\n", "| 1 | 0.0290003411805 | 0.00785245593332 |\n", "| 2 | 0.0259297168202 | 0.0146674930324 |\n", "| 3 | 0.0233139997725 | 0.0200522244918 |\n", "| 4 | 0.0220914363698 | 0.0254947866371 |\n", "| 5 | 0.0205390651655 | 0.029465502225 |\n", "| 6 | 0.0193904242011 | 0.0328532078133 |\n", "| 7 | 0.0182287858849 | 0.0358179825284 |\n", "| 8 | 0.0176987376322 | 0.0398154805381 |\n", "| 9 | 0.0167557526821 | 0.0422040061866 |\n", "| 10 | 0.0158990105766 | 0.0442755945172 |\n", "+--------+-----------------+------------------+\n", "[10 rows x 3 columns]\n", "\n", "PROGRESS: Evaluate model M1\n", "PROGRESS: recommendations finished on 1000/2931 queries. users per second: 998.277\n", "PROGRESS: recommendations finished on 2000/2931 queries. users per second: 1001.05\n", "\n", "Precision and recall summary statistics by cutoff\n", "+--------+-----------------+-----------------+\n", "| cutoff | mean_precision | mean_recall |\n", "+--------+-----------------+-----------------+\n", "| 1 | 0.1890139884 | 0.0606302659015 |\n", "| 2 | 0.159672466735 | 0.0972997069082 |\n", "| 3 | 0.140680086432 | 0.124672622101 |\n", "| 4 | 0.127430910952 | 0.148397927748 |\n", "| 5 | 0.114909587172 | 0.166310413969 |\n", "| 6 | 0.105140452633 | 0.180875146689 |\n", "| 7 | 0.0974801384218 | 0.195202556078 |\n", "| 8 | 0.0917349027636 | 0.210141411907 |\n", "| 9 | 0.0860912089162 | 0.222035810393 |\n", "| 10 | 0.0812691914023 | 0.232211466743 |\n", "+--------+-----------------+-----------------+\n", "[10 rows x 3 columns]\n", "\n", "Model compare metric: precision_recall\n" ] } ], "source": [ "model_performance = graphlab.compare(test_data, \n", " [popularity_model, personalized_model],\n", " user_sample=.05)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Quantitative comparison between the models\n", "We now formally compare the popularity and the personalized models using precision-recall curves." ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "collapsed": false }, "outputs": [ { "data": { "application/javascript": [ "$(\"head\").append($(\"\").attr({\n", " rel: \"stylesheet\",\n", " type: \"text/css\",\n", " href: \"//cdnjs.cloudflare.com/ajax/libs/font-awesome/4.1.0/css/font-awesome.min.css\"\n", "}));\n", "$(\"head\").append($(\"\").attr({\n", " rel: \"stylesheet\",\n", " type: \"text/css\",\n", " href: \"//dato.com/files/canvas/1.8.1/css/canvas.css\"\n", "}));\n", "\n", " (function(){\n", "\n", " var e = null;\n", " if (typeof element == 'undefined') {\n", " var scripts = document.getElementsByTagName('script');\n", " var thisScriptTag = scripts[scripts.length-1];\n", " var parentDiv = thisScriptTag.parentNode;\n", " e = document.createElement('div');\n", " parentDiv.appendChild(e);\n", " } else {\n", " e = element[0];\n", " }\n", "\n", " if (typeof requirejs !== 'undefined') {\n", " // disable load timeout; ipython_app.js is large and can take a while to load.\n", " requirejs.config({waitSeconds: 0});\n", " }\n", "\n", " require(['//dato.com/files/canvas/1.8.1/js/ipython_app.js'], function(IPythonApp){\n", " var app = new IPythonApp();\n", " app.attachView('model','Comparison', {\"comparison\": {\"dataset_label\": \"test_data\", \"evaluations\": {\"popularity_model\": {\"precision_recall\": [{\"cutoff\": 1, \"precision\": 0.02900034118048454, \"recall\": 0.007852455933315725}, {\"cutoff\": 2, \"precision\": 0.025929716820197925, \"recall\": 0.014667493032385539}, {\"cutoff\": 3, \"precision\": 0.02331399977254641, \"recall\": 0.020052224491835538}, {\"cutoff\": 4, \"precision\": 0.02209143636983968, \"recall\": 0.02549478663708898}, {\"cutoff\": 5, \"precision\": 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"metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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user_idsong_idlisten_counttitleartist
b80344d063b5ccb3212f76538
f3d9e43d87dca9e ...		SOAKIMP12A8C1309951The CoveJack Johnson
b80344d063b5ccb3212f76538
f3d9e43d87dca9e ...		SOBBMDR12A8C13253B2Entre Dos AguasPaco De Lucia
b80344d063b5ccb3212f76538
f3d9e43d87dca9e ...		SOBXHDL12A81C204C01StrongerKanye West
b80344d063b5ccb3212f76538
f3d9e43d87dca9e ...		SOBYHAJ12A6701BF1D1ConstellationsJack Johnson
b80344d063b5ccb3212f76538
f3d9e43d87dca9e ...		SODACBL12A8C13C2731Learn To FlyFoo Fighters
b80344d063b5ccb3212f76538
f3d9e43d87dca9e ...		SODDNQT12A6D4F5F7E5Apuesta Por El Rock 'N'
Roll ...		Héroes del Silencio
b80344d063b5ccb3212f76538
f3d9e43d87dca9e ...		SODXRTY12AB0180F3B1Paper GangstaLady GaGa
b80344d063b5ccb3212f76538
f3d9e43d87dca9e ...		SOFGUAY12AB017B0A81Stacked ActorsFoo Fighters
b80344d063b5ccb3212f76538
f3d9e43d87dca9e ...		SOFRQTD12A81C233C01Sehr kosmischHarmonia
b80344d063b5ccb3212f76538
f3d9e43d87dca9e ...		SOHQWYZ12A6D4FA7011Heaven's gonna burn your
eyes ...		Thievery Corporation
feat. Emiliana Torrini ...
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song
The Cove - Jack Johnson
Entre Dos Aguas - Paco De
Lucia ...
Stronger - Kanye West
Constellations - Jack
Johnson ...
Learn To Fly - Foo
Fighters ...
Apuesta Por El Rock 'N'
Roll - Héroes del ...
Paper Gangsta - Lady GaGa
Stacked Actors - Foo
Fighters ...
Sehr kosmisch - Harmonia
Heaven's gonna burn your
eyes - Thievery ...
\n", "[10 rows x 6 columns]
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" ], "text/plain": [ "Columns:\n", "\tuser_id\tstr\n", "\tsong_id\tstr\n", "\tlisten_count\tint\n", "\ttitle\tstr\n", "\tartist\tstr\n", "\tsong\tstr\n", "\n", "Rows: 10\n", "\n", "Data:\n", "+-------------------------------+--------------------+--------------+\n", "| user_id | song_id | listen_count |\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", "+-------------------------------+-------------------------------+\n", "| title | artist |\n", "+-------------------------------+-------------------------------+\n", "| The Cove | Jack Johnson |\n", "| Entre Dos Aguas | Paco De Lucia |\n", "| Stronger | Kanye West |\n", "| Constellations | Jack Johnson |\n", "| Learn To Fly | Foo Fighters |\n", "| Apuesta Por El Rock 'N' Roll | Héroes del Silencio |\n", "| Paper Gangsta | Lady GaGa |\n", "| Stacked Actors | Foo Fighters |\n", "| Sehr kosmisch | Harmonia |\n", "| Heaven's gonna burn your eyes | Thievery Corporation feat.... |\n", "+-------------------------------+-------------------------------+\n", "+-------------------------------+\n", "| song |\n", "+-------------------------------+\n", "| The Cove - Jack Johnson |\n", "| Entre Dos Aguas - Paco De ... |\n", "| Stronger - Kanye West |\n", "| Constellations - Jack Johnson |\n", "| Learn To Fly - Foo Fighters |\n", "| Apuesta Por El Rock 'N' Ro... |\n", "| Paper Gangsta - Lady GaGa |\n", "| Stacked Actors - Foo Fighters |\n", "| Sehr kosmisch - Harmonia |\n", "| Heaven's gonna burn your e... |\n", "+-------------------------------+\n", "[10 rows x 6 columns]" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "song_data.head()" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# Home work\n", "\n", "west = song_data[song_data['artist'] == 'Kanye West']\n", "fighters = song_data[song_data['artist'] == 'Foo Fighters']\n", "swift = song_data[song_data['artist'] == 'Taylor Swift']\n", "gaga = song_data[song_data['artist'] == 'Lady GaGa']" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "west: 2522\n", "fighters: 2055\n", "swift: 3246\n", "gaga: 2928\n" ] } ], "source": [ "print 'west: ', len(west['user_id'].unique())\n", "print 'fighters: ', len(fighters['user_id'].unique())\n", "print 'swift: ', len(swift['user_id'].unique())\n", "print 'gaga: ', len(gaga['user_id'].unique())" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "collapsed": false }, "outputs": [], "source": [ "total_count_table = song_data.groupby(key_columns='artist', operations={'total_count': graphlab.aggregate.SUM('listen_count')})" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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artisttotal_count
Kings Of Leon43218
Dwight Yoakam40619
Björk38889
Coldplay35362
Florence + The Machine33387
Justin Bieber29715
Alliance Ethnik26689
OneRepublic25754
Train25402
The Black Keys22184
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Note: Only the head of the SFrame is printed.
You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.\n", "
" ], "text/plain": [ "Columns:\n", "\tartist\tstr\n", "\ttotal_count\tint\n", "\n", "Rows: 3375\n", "\n", "Data:\n", "+------------------------+-------------+\n", "| artist | total_count |\n", "+------------------------+-------------+\n", "| Kings Of Leon | 43218 |\n", "| Dwight Yoakam | 40619 |\n", "| Björk | 38889 |\n", "| Coldplay | 35362 |\n", "| Florence + The Machine | 33387 |\n", "| Justin Bieber | 29715 |\n", "| Alliance Ethnik | 26689 |\n", "| OneRepublic | 25754 |\n", "| Train | 25402 |\n", "| The Black Keys | 22184 |\n", "+------------------------+-------------+\n", "[3375 rows x 2 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": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "total_count_table.sort('total_count', ascending=False)" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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artisttotal_count
William Tabbert14
Reel Feelings24
Beyoncé feat. Bun B and
Slim Thug ...		26
Diplo30
Boggle Karaoke30
harvey summers31
Nâdiya36
Kanye West / Talib Kweli
/ Q-Tip / Common / ...		38
Aneta Langerova38
Jody Bernal38
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Note: Only the head of the SFrame is printed.
You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.\n", "
" ], "text/plain": [ "Columns:\n", "\tartist\tstr\n", "\ttotal_count\tint\n", "\n", "Rows: 3375\n", "\n", "Data:\n", "+-------------------------------+-------------+\n", "| artist | total_count |\n", "+-------------------------------+-------------+\n", "| William Tabbert | 14 |\n", "| Reel Feelings | 24 |\n", "| Beyoncé feat. Bun B and Sl... | 26 |\n", "| Diplo | 30 |\n", "| Boggle Karaoke | 30 |\n", "| harvey summers | 31 |\n", "| Nâdiya | 36 |\n", "| Kanye West / Talib Kweli /... | 38 |\n", "| Aneta Langerova | 38 |\n", "| Jody Bernal | 38 |\n", "+-------------------------------+-------------+\n", "[3375 rows x 2 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": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "total_count_table.sort('total_count', ascending=True)" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "collapsed": true }, "outputs": [], "source": [ "subset_test_users = test_data['user_id'].unique()[0:10000]" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "PROGRESS: recommendations finished on 1000/10000 queries. users per second: 1128.23\n", "PROGRESS: recommendations finished on 2000/10000 queries. users per second: 1211.72\n", "PROGRESS: recommendations finished on 3000/10000 queries. users per second: 1250.5\n", "PROGRESS: recommendations finished on 4000/10000 queries. users per second: 1260.36\n", "PROGRESS: recommendations finished on 5000/10000 queries. users per second: 1213.34\n", "PROGRESS: recommendations finished on 6000/10000 queries. users per second: 1109.96\n", "PROGRESS: recommendations finished on 7000/10000 queries. users per second: 1080.68\n", "PROGRESS: recommendations finished on 8000/10000 queries. users per second: 1098.41\n", "PROGRESS: recommendations finished on 9000/10000 queries. users per second: 1111.26\n", "PROGRESS: recommendations finished on 10000/10000 queries. users per second: 1111.68\n" ] } ], "source": [ "recommeded_songs = personalized_model.recommend(subset_test_users, k=1)" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "collapsed": false }, "outputs": [], "source": [ "#recommeded_songs.head()" ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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songcount
Undo - Björk431
Secrets - OneRepublic383
Revelry - Kings Of Leon232
You're The One - Dwight
Yoakam ...		170
Fireflies - Charttraxx
Karaoke ...		123
Hey_ Soul Sister - Train107
Horn Concerto No. 4 in E
flat K495: II. Romance ...		99
Sehr kosmisch - Harmonia71
OMG - Usher featuring
will.i.am ...		58
Dog Days Are Over (Radio
Edit) - Florence + The ...		53
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Note: Only the head of the SFrame is printed.
You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.\n", "
" ], "text/plain": [ "Columns:\n", "\tsong\tstr\n", "\tcount\tint\n", "\n", "Rows: 3134\n", "\n", "Data:\n", "+--------------------------------+-------+\n", "| song | count |\n", "+--------------------------------+-------+\n", "| Undo - Björk | 431 |\n", "| Secrets - OneRepublic | 383 |\n", "| Revelry - Kings Of Leon | 232 |\n", "| You're The One - Dwight Yoakam | 170 |\n", "| Fireflies - Charttraxx Karaoke | 123 |\n", "| Hey_ Soul Sister - Train | 107 |\n", "| Horn Concerto No. 4 in E f... | 99 |\n", "| Sehr kosmisch - Harmonia | 71 |\n", "| OMG - Usher featuring will... | 58 |\n", "| Dog Days Are Over (Radio E... | 53 |\n", "+--------------------------------+-------+\n", "[3134 rows x 2 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": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "recommeded_songs.groupby(key_columns='song', operations={'count': graphlab.aggregate.COUNT()})\\\n", ".sort('count', ascending=False)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.11" } }, "nbformat": 4, "nbformat_minor": 0 }