http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/blob/c2c7b62a/demo/supervisedlearning/index.html ---------------------------------------------------------------------- diff --git a/demo/supervisedlearning/index.html b/demo/supervisedlearning/index.html index 21d288b..fc34158 100644 --- a/demo/supervisedlearning/index.html +++ b/demo/supervisedlearning/index.html @@ -1,4 +1,4 @@ -<!DOCTYPE html><html><head><title>Machine Learning With PredictionIO</title><meta charset="utf-8"/><meta content="IE=edge,chrome=1" http-equiv="X-UA-Compatible"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><meta class="swiftype" name="title" data-type="string" content="Machine Learning With PredictionIO"/><link rel="canonical" href="https://docs.prediction.io/demo/supervisedlearning/"/><link href="/images/favicon/normal-b330020a.png" rel="shortcut icon"/><link href="/images/favicon/apple-c0febcf2.png" rel="apple-touch-icon"/><link 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id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/apache/incubator-predictionio/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row"><div class="row"><div class="col-md-9 col-sm-11 c ol-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Machine Learning With PredictionIO</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container-fluid"><div class="row"><d iv id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Integ rating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li 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href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluatio n Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="/gallery/template-gallery/"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li clas s="level-2"><a class="final" href="/demo/community/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul> <li class="level-2"><a class="final" href="/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Machine Learning With PredictionIO</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#introduction-to-supervised-learning">Introduction to Supervised Learning</a> </li> <li> <a href="#predictionio-and-supervis ed-learning">PredictionIO and Supervised Learning</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/demo/supervisedlearning.html.md";><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Machine Learning With PredictionIO</h1></div></div><div class="content"><p>This guide is designed to give developers a brief introduction to fundamental concepts in machine learning, as well as an explanation of how these concept tie into PredictionIO's engine development platform. This particular guide will largely deal with giving some </p><h2 id='introduction-to-supervised-learning' class='header-anchors'>Introduction to Supervised Learning</h2><p>The first question we must ask is: what is machine learning? <strong>Machine learning</strong> is the field of study at the intersection of computer science, engineerin g, mathematics, and statistics which seeks to discover or infer patterns hidden within a set of observations, which we call our data. Some examples of problems that machine learning seeks to solve are:</p> <ul> <li>Predict whether a patient has breast cancer based on their mammogram results.</li> <li>Predict whether an e-mail is spam or not based on the e-mail's content.</li> <li>Predict today's temperature based on climate variables collected for the previous week.</li> </ul> <h3 id='thinking-about-data' class='header-anchors'>Thinking About Data</h3><p>In the latter examples, we are trying to predict an outcome \(Y\), or <strong>response</strong>, based on some recorded or observed variables \(X\), or <strong>features</strong>. For example: in the third problem each observation is a patient, the response variable \(Y\) is equal to 1 if this patient has breast cancer and 0 otherwise, and \(X\) represents the mammogram results. </p><p>When we say we want to predict \(Y\) usi ng \(X\), we are trying to answer the question: how does a response \(Y\) depend on a set of features \(X\) affect the response \(Y\)? To do this we need a set of observations, which we call our <strong>training data</strong>, consisting of observations for which we have observed both \(Y\) and \(X\), in order to make inference about this relationship. </p><h3 id='different-types-of-supervised-learning-problems' class='header-anchors'>Different Types of Supervised Learning Problems</h3><p>Note that in the first two examples, the outcome \(Y\) can only take on two values (1 : cancer/spam, 0: no cancer/ no spam). Whenever the outcome variable \(Y\) denotes a label associated to a particular group of observations (i.e. cancer group), the <strong>supervised learning</strong> problem is also called a <strong>classification</strong> problem. In the third example, however, \(Y\) can take on any numerical value since it denotes some temperature reading (i.e. 25.143, 25.14233, 32.0). These t ypes of supervised learning problems are also called <strong>regression</strong> problems.</p><h3 id='training-a-predictive-model' class='header-anchors'>Training a Predictive Model</h3><p>A predictive model should be thought of as a function \(f\) that takes as input a set of features, and outputs a predicted outcome (i.e. \(f(X) = Y\)). The phrase <strong>training a model</strong> simply refers to the process of using the training data to estimate such a function. </p><h2 id='predictionio-and-supervised-learning' class='header-anchors'>PredictionIO and Supervised Learning</h2><p>Machine learning methods generally assume that our observation responses and features are numeric vectors. We will say that observations in this format are in <strong>standard form</strong>. However, when you are working with real-life data this will often not be the case. The data will often be formatted in a manner that is specific to the application's needs. As an example, let's suppose our appl ication is <a href="http://stackoverflow.com";>StackOverFlow</a>. The data we want to analyze are questions, and we want to predict based on a question's content whether or not it is related to Scala. </p><p><strong>Self-check:</strong> Is this a classification or regression problem?</p><h3 id='thinking-about-data-with-predictionio' class='header-anchors'>Thinking About Data With PredictionIO</h3><p>PredictionIO's predictive engine development platform allows you to easily incorporate observations that are not in standard form. Continuing with our example, we can import the observations, or StackOverFlow questions, into <a href="/datacollection/">PredictionIO's Event Server</a> as events with the following properties:</p><p><code>properties = {question : String, topic : String}</code></p><p>The value <code>question</code> is the actual question stored as a <code>String</code>, and topic is also a string equal to either <code>"Scala"</code> or <code>"Other&q uot;</code>. Our outcome here is <code>topic</code>, and <code>question</code> will provide a source for extracting features. That is, we will be using <code>question</code> to predict the outcome <code>topic</code>.</p><p>Once the observations are loaded as events into the Event Server, the engine's <a href="/customize/">Data Source</a> component is able to read them, which allows you to treat them as objects in a Scala project. The engine's Preparator component is in charge of converting these observations into standard form. To do this, we can first map the topic values as follows:</p><p><code>Map("Other" -> 0, "Scala" -> 1)</code>.</p><p>We can then vectorize the observation's associated question text to obtain a numeric feature vector for each of our observations. This text vectorization procedure is an example of a general concept in machine learning called <strong>feature extraction</strong>. After performing these transformations of our observations, they are now in standard form and can be used for training a large quantity of machine learning models.</p><h3 id='training-the-model-with-predictionio' class='header-anchors'>Training the Model With PredictionIO</h3><p>The Algorithm engine component serves two purposes: outputting a predictive model \(f\) and using this to predict the outcome variable. Here \(f\) takes as input a vectorized question and outputs either 0 or 1. However, our <code>Query</code> input will be again a question, and our <code>PredictedResult</code> the topic associated to the predicted label (0 or 1):</p><p><code>Query = {question : String}</code> <code>PredictedResult = {topic : String}</code></p><p>With PredictionIO's engine development platform, you can easily automate the vectorization of the Query question, as well as mapping the predicted label to the appropriate topic output format.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class=" row"><div class="col-md-6 col-xs-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="//docs.prediction.io/install/" target="blank">Download</a></li><li><a href="//docs.prediction.io/" target="blank">Docs</a></li><li><a href="//github.com/apache/incubator-predictionio" target="blank">GitHub</a></li><li><a href="mailto:[email protected]"; target="blank">Subscribe to User Mailing List</a></li><li><a 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class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container-fluid"><div class="row"><di v id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Integr ating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Engine Command-line Interfac e</span></a></li><li class="level-2"><a class="final" href="/deploy/monitoring/"><span>Monitoring Engine</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li c lass="level-2"><a class="final" href="/datacollection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="/gallery/template-gallery/"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class ="level-2"><a class="final" href="/demo/community/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul>< li class="level-2"><a class="final" href="/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Machine Learning With PredictionIO</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#introduction-to-supervised-learning">Introduction to Supervised Learning</a> </li> <li> <a href="#predictionio-and-supervise d-learning">PredictionIO and Supervised Learning</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/demo/supervisedlearning.html.md";><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Machine Learning With PredictionIO</h1></div></div><div class="content"><p>This guide is designed to give developers a brief introduction to fundamental concepts in machine learning, as well as an explanation of how these concept tie into PredictionIO's engine development platform. This particular guide will largely deal with giving some </p><h2 id='introduction-to-supervised-learning' class='header-anchors'>Introduction to Supervised Learning</h2><p>The first question we must ask is: what is machine learning? <strong>Machine learning</strong> is the field of study at the intersection of computer science, engineering , mathematics, and statistics which seeks to discover or infer patterns hidden within a set of observations, which we call our data. Some examples of problems that machine learning seeks to solve are:</p> <ul> <li>Predict whether a patient has breast cancer based on their mammogram results.</li> <li>Predict whether an e-mail is spam or not based on the e-mail's content.</li> <li>Predict today's temperature based on climate variables collected for the previous week.</li> </ul> <h3 id='thinking-about-data' class='header-anchors'>Thinking About Data</h3><p>In the latter examples, we are trying to predict an outcome \(Y\), or <strong>response</strong>, based on some recorded or observed variables \(X\), or <strong>features</strong>. For example: in the third problem each observation is a patient, the response variable \(Y\) is equal to 1 if this patient has breast cancer and 0 otherwise, and \(X\) represents the mammogram results. </p><p>When we say we want to predict \(Y\) usin g \(X\), we are trying to answer the question: how does a response \(Y\) depend on a set of features \(X\) affect the response \(Y\)? To do this we need a set of observations, which we call our <strong>training data</strong>, consisting of observations for which we have observed both \(Y\) and \(X\), in order to make inference about this relationship. </p><h3 id='different-types-of-supervised-learning-problems' class='header-anchors'>Different Types of Supervised Learning Problems</h3><p>Note that in the first two examples, the outcome \(Y\) can only take on two values (1 : cancer/spam, 0: no cancer/ no spam). Whenever the outcome variable \(Y\) denotes a label associated to a particular group of observations (i.e. cancer group), the <strong>supervised learning</strong> problem is also called a <strong>classification</strong> problem. In the third example, however, \(Y\) can take on any numerical value since it denotes some temperature reading (i.e. 25.143, 25.14233, 32.0). These ty pes of supervised learning problems are also called <strong>regression</strong> problems.</p><h3 id='training-a-predictive-model' class='header-anchors'>Training a Predictive Model</h3><p>A predictive model should be thought of as a function \(f\) that takes as input a set of features, and outputs a predicted outcome (i.e. \(f(X) = Y\)). The phrase <strong>training a model</strong> simply refers to the process of using the training data to estimate such a function. </p><h2 id='predictionio-and-supervised-learning' class='header-anchors'>PredictionIO and Supervised Learning</h2><p>Machine learning methods generally assume that our observation responses and features are numeric vectors. We will say that observations in this format are in <strong>standard form</strong>. However, when you are working with real-life data this will often not be the case. The data will often be formatted in a manner that is specific to the application's needs. As an example, let's suppose our appli cation is <a href="http://stackoverflow.com";>StackOverFlow</a>. The data we want to analyze are questions, and we want to predict based on a question's content whether or not it is related to Scala. </p><p><strong>Self-check:</strong> Is this a classification or regression problem?</p><h3 id='thinking-about-data-with-predictionio' class='header-anchors'>Thinking About Data With PredictionIO</h3><p>PredictionIO's predictive engine development platform allows you to easily incorporate observations that are not in standard form. Continuing with our example, we can import the observations, or StackOverFlow questions, into <a href="/datacollection/">PredictionIO's Event Server</a> as events with the following properties:</p><p><code>properties = {question : String, topic : String}</code></p><p>The value <code>question</code> is the actual question stored as a <code>String</code>, and topic is also a string equal to either <code>"Scala"</code> or <code>"Other&qu ot;</code>. Our outcome here is <code>topic</code>, and <code>question</code> will provide a source for extracting features. That is, we will be using <code>question</code> to predict the outcome <code>topic</code>.</p><p>Once the observations are loaded as events into the Event Server, the engine's <a href="/customize/">Data Source</a> component is able to read them, which allows you to treat them as objects in a Scala project. The engine's Preparator component is in charge of converting these observations into standard form. To do this, we can first map the topic values as follows:</p><p><code>Map("Other" -> 0, "Scala" -> 1)</code>.</p><p>We can then vectorize the observation's associated question text to obtain a numeric feature vector for each of our observations. This text vectorization procedure is an example of a general concept in machine learning called <strong>feature extraction</strong>. After performing these transformations of our o bservations, they are now in standard form and can be used for training a large quantity of machine learning models.</p><h3 id='training-the-model-with-predictionio' class='header-anchors'>Training the Model With PredictionIO</h3><p>The Algorithm engine component serves two purposes: outputting a predictive model \(f\) and using this to predict the outcome variable. Here \(f\) takes as input a vectorized question and outputs either 0 or 1. However, our <code>Query</code> input will be again a question, and our <code>PredictedResult</code> the topic associated to the predicted label (0 or 1):</p><p><code>Query = {question : String}</code> <code>PredictedResult = {topic : String}</code></p><p>With PredictionIO's engine development platform, you can easily automate the vectorization of the Query question, as well as mapping the predicted label to the appropriate topic output format.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="r ow"><div class="col-md-6 col-xs-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="//docs.prediction.io/install/" target="blank">Download</a></li><li><a href="//docs.prediction.io/" target="blank">Docs</a></li><li><a href="//github.com/apache/incubator-predictionio" target="blank">GitHub</a></li><li><a href="mailto:[email protected]"; target="blank">Subscribe to User Mailing List</a></li><li><a href="//stackoverflow.com/questions/tagged/predictionio" target="blank">Stackoverflow</a></li></ul></div></div><div class="col-md-6 col-xs-6 footer-link-column"><div class="footer-link-column-row"><h4>Contribute</h4><ul><li><a href="//predictionio.incubator.apache.org/community/contribute-code/" target="blank">Contribute</a></li><li><a href="//github.com/apache/incubator-predictionio" target="blank">Source Code</a></li><li><a href="//issues.apache.org/jira/browse/PIO" target="blank">Bug Tracker</a></li><li><a href="mailto :[email protected]" target="blank">Subscribe to Development Mailing List</a></li></ul></div></div></div></div><div id="footer-bottom"><div class="container"><div class="row"><div class="col-md-12"><div id="footer-logo-wrapper"><img alt="PredictionIO" src="/images/logos/logo-white-d1e9c6e6.png"/></div><div id="social-icons-wrapper"><a class="github-button" href="https://github.com/apache/incubator-predictionio"; data-style="mega" data-count-href="/apache/incubator-predictionio/stargazers" data-count-api="/repos/apache/incubator-predictionio#stargazers_count" data-count-aria-label="# stargazers on GitHub" aria-label="Star apache/incubator-predictionio on GitHub">Star</a> <a class="github-button" href="https://github.com/apache/incubator-predictionio/fork"; data-icon="octicon-git-branch" data-style="mega" data-count-href="/apache/incubator-predictionio/network" data-count-api="/repos/apache/incubator-predictionio#forks_count" data-count-aria-label="# forks o n GitHub" aria-label="Fork apache/incubator-predictionio on GitHub">Fork</a> <script id="github-bjs" async="" defer="" src="https://buttons.github.io/buttons.js";></script><a href="//www.facebook.com/predictionio" target="blank"><img alt="PredictionIO on Twitter" src="/images/icons/twitter-ea9dc152.png"/></a> <a href="//twitter.com/predictionio" target="blank"><img alt="PredictionIO on Facebook" src="/images/icons/facebook-5c57939c.png"/></a> </div></div></div></div></div></footer></div><script>(function(w,d,t,u,n,s,e){w['SwiftypeObject']=n;w[n]=w[n]||function(){ (w[n].q=w[n].q||[]).push(arguments);};s=d.createElement(t); e=d.getElementsByTagName(t)[0];s.async=1;s.src=u;e.parentNode.insertBefore(s,e); })(window,document,'script','//s.swiftypecdn.com/install/v1/st.js','_st');
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id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://predictionio.incubator.apache.org/";><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/apache/incubator-predictionio/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row"><div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidde n-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Comics Recommendation Demo</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="co l-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul> <li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level- 2"><a class="final" href="/deploy/monitoring/"><span>Monitoring Engine</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" hr ef="/datacollection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class= "level-2"><a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="/gallery/template-gallery/"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final active" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class ="final" href="/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Demo Tutorials</a><span class="spacer">></span></li><li><span class="last">Comics Recommendation Demo</span></li></ul></div><div id="page-title"><h1>Comics Recommendation Demo</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="t able-of-contents"><ul> <li> <a href="#introduction">Introduction</a> </li> <li> <a href="#tapster-demo-application">Tapster Demo Application</a> </li> <li> <a href="#apache-predictionio-incubating-setup">Apache PredictionIO (incubating) Setup</a> </li> <li> <a href="#import-data">Import Data</a> </li> <li> <a href="#connect-demo-app-with-apache-predictionio-incubating">Connect Demo app with Apache PredictionIO (incubating)</a> </li> <li> <a href="#links">Links</a> </li> <li> <a href="#conclusion">Conclusion</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/demo/tapster.html.md";><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Demo Tutorials</a><span class="spacer">></span></li><li><span class="last">Comics Recommendation Demo</span></li></ul></div><di v id="page-title"><h1>Comics Recommendation Demo</h1></div></div><div class="content"><h2 id='introduction' class='header-anchors'>Introduction</h2><p>In this demo, we will show you how to build a Tinder-style web application (named "Tapster") recommending comics to users based on their likes/dislikes of episodes interactively.</p><p>The demo will use <a href="https://docs.prediction.io/templates/similarproduct/quickstart/";>Similar Product Template</a>. Similar Product Template is a great choice if you want to make recommendations based on immediate user activities or for new users with limited history. It uses MLLib Alternating Least Squares (ALS) recommendation algorithm, a <a href="http://en.wikipedia.org/wiki/Recommender_system#Collaborative_filtering";>Collaborative filtering</a> (CF) algorithm commonly used for recommender systems. These techniques aim to fill in the missing entries of a user-item association matrix. Users and products are described by a small set of latent factors that can be used to predict missing entries. A layman's interpretation of Collaborative Filtering is "People who like this comic, also like these comics."</p><p>All the code and data is on GitHub at: <a href="https://github.com/PredictionIO/Demo-Tapster";>github.com/PredictionIO/Demo-Tapster</a>.</p><h3 id='data' class='header-anchors'>Data</h3><p>The source of the data is from <a href="http://tapastic.com/";>Tapastic</a>. You can find the data files <a href="https://github.com/PredictionIO/Demo-Tapster/tree/master/data";>here</a>.</p><p>The data structure looks like this:</p><p><a href="https://github.com/PredictionIO/Demo-Tapster/blob/master/data/episode_list.csv";>Episode List</a> <code>data/episode_list.csv</code></p><p><strong>Fields:</strong> episodeId | episodeTitle | episodeCategories | episodeUrl | episodeImageUrls</p><p>1,000 rows. Each row represents one episode.</p><p><a href="https://github.com/PredictionIO/Demo-Tapster/blob/master/data/user_lis t.csv">User Like Event List</a> <code>data/user_list.csv</code></p><p><strong>Fields:</strong> userId | episodeId | likedTimestamp</p><p>192,587 rows. Each row represents one user like for the given episode.</p><p>The tutorial has four major steps:</p> <ul> <li>Demo application setup</li> <li>PredictionIO installation and setup</li> <li>Import data into database and PredictionIO</li> <li>Integrate demo application with PredictionIO</li> </ul> <h2 id='tapster-demo-application' class='header-anchors'>Tapster Demo Application</h2><p>The demo application is built using Rails.</p><p>You can clone the existing application with:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1 +<!DOCTYPE html><html><head><title>Comics Recommendation Demo</title><meta charset="utf-8"/><meta content="IE=edge,chrome=1" http-equiv="X-UA-Compatible"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><meta class="swiftype" name="title" data-type="string" content="Comics Recommendation Demo"/><link rel="canonical" href="https://docs.prediction.io/demo/tapster/"/><link href="/images/favicon/normal-b330020a.png" rel="shortcut icon"/><link href="/images/favicon/apple-c0febcf2.png" rel="apple-touch-icon"/><link href="//fonts.googleapis.com/css?family=Open+Sans:300italic,400italic,600italic,700italic,800italic,400,300,600,700,800" rel="stylesheet"/><link href="//maxcdn.bootstrapcdn.com/font-awesome/4.2.0/css/font-awesome.min.css" rel="stylesheet"/><link href="/stylesheets/application-a2a2f408.css" rel="stylesheet" type="text/css"/><script src="//cdnjs.cloudflare.com/ajax/libs/html5shiv/3.7.2/html5shiv.min.js"></script><script src="//cdn.mathjax.org/mathjax/latest/ MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script><script src="//use.typekit.net/pqo0itb.js"></script><script>try{Typekit.load({ async: true });}catch(e){}</script></head><body><div id="global"><header><div class="container" id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://predictionio.incubator.apache.org/";><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="pill-wrapper"><a class="pill left" href="/gallery/template-gallery">TEMPLATES</a> <a class="pill right" href="//github.com/apache/incubator-predictionio/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row"><div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden -md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Comics Recommendation Demo</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col -md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul>< li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2 "><a class="final" href="/deploy/monitoring/"><span>Monitoring Engine</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" hre f="/datacollection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li c lass="level-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class=" level-2"><a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="/gallery/template-gallery/"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final active" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class= "final" href="/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Demo Tutorials</a><span class="spacer">></span></li><li><span class="last">Comics Recommendation Demo</span></li></ul></div><div id="page-title"><h1>Comics Recommendation Demo</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="ta ble-of-contents"><ul> <li> <a href="#introduction">Introduction</a> </li> <li> <a href="#tapster-demo-application">Tapster Demo Application</a> </li> <li> <a href="#apache-predictionio-incubating-setup">Apache PredictionIO (incubating) Setup</a> </li> <li> <a href="#import-data">Import Data</a> </li> <li> <a href="#connect-demo-app-with-apache-predictionio-incubating">Connect Demo app with Apache PredictionIO (incubating)</a> </li> <li> <a href="#links">Links</a> </li> <li> <a href="#conclusion">Conclusion</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/demo/tapster.html.md";><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Demo Tutorials</a><span class="spacer">></span></li><li><span class="last">Comics Recommendation Demo</span></li></ul></div><div id="page-title"><h1>Comics Recommendation Demo</h1></div></div><div class="content"><h2 id='introduction' class='header-anchors'>Introduction</h2><p>In this demo, we will show you how to build a Tinder-style web application (named "Tapster") recommending comics to users based on their likes/dislikes of episodes interactively.</p><p>The demo will use <a href="https://docs.prediction.io/templates/similarproduct/quickstart/";>Similar Product Template</a>. Similar Product Template is a great choice if you want to make recommendations based on immediate user activities or for new users with limited history. It uses MLLib Alternating Least Squares (ALS) recommendation algorithm, a <a href="http://en.wikipedia.org/wiki/Recommender_system#Collaborative_filtering";>Collaborative filtering</a> (CF) algorithm commonly used for recommender systems. These techniques aim to fill in the missing entries of a user-item association matrix. Users and products are described by a small set of l atent factors that can be used to predict missing entries. A layman's interpretation of Collaborative Filtering is "People who like this comic, also like these comics."</p><p>All the code and data is on GitHub at: <a href="https://github.com/PredictionIO/Demo-Tapster";>github.com/PredictionIO/Demo-Tapster</a>.</p><h3 id='data' class='header-anchors'>Data</h3><p>The source of the data is from <a href="http://tapastic.com/";>Tapastic</a>. You can find the data files <a href="https://github.com/PredictionIO/Demo-Tapster/tree/master/data";>here</a>.</p><p>The data structure looks like this:</p><p><a href="https://github.com/PredictionIO/Demo-Tapster/blob/master/data/episode_list.csv";>Episode List</a> <code>data/episode_list.csv</code></p><p><strong>Fields:</strong> episodeId | episodeTitle | episodeCategories | episodeUrl | episodeImageUrls</p><p>1,000 rows. Each row represents one episode.</p><p><a href="https://github.com/PredictionIO/Demo-Tapster/blob/master/data/user_list .csv">User Like Event List</a> <code>data/user_list.csv</code></p><p><strong>Fields:</strong> userId | episodeId | likedTimestamp</p><p>192,587 rows. Each row represents one user like for the given episode.</p><p>The tutorial has four major steps:</p> <ul> <li>Demo application setup</li> <li>PredictionIO installation and setup</li> <li>Import data into database and PredictionIO</li> <li>Integrate demo application with PredictionIO</li> </ul> <h2 id='tapster-demo-application' class='header-anchors'>Tapster Demo Application</h2><p>The demo application is built using Rails.</p><p>You can clone the existing application with:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1 2 3</pre></td><td class="code"><pre><span class="gp">$ </span>git clone https://github.com/PredictionIO/Demo-Tapster.git <span class="gp">$ </span><span class="nb">cd </span>Demo-Tapster http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/blob/c2c7b62a/demo/tapster/index.html.gz ---------------------------------------------------------------------- diff --git a/demo/tapster/index.html.gz b/demo/tapster/index.html.gz index 54dfdbc..aacee1a 100644 Binary files a/demo/tapster/index.html.gz and b/demo/tapster/index.html.gz differ
