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 able-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#defining-metric">Defining Metric</a> </li> <li> <a href="#common-metrics">Common Metrics</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/predictionio/tree/livedoc/docs/manual/source/evaluation/metricchoose.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="#">Tuning and Evaluation</a><span class="spacer">&gt;</span></li><li><span class="last">Choosing Evaluation Metrics</span></li></ul></div><div id="page-title"><h1>Choosing Evaluation Metrics</h1></div></div><div class="content"> <p>The <a href="/evaluation/paramtuning/">hyperparameter tuning module</a> allows us to select the optimal engine parameter defined by a <code>Metric</code>. <code>Metric</code> determines the quality of an engine variant. We have 
 skimmed through the process of choosing the right <code>Metric</code> in previous sections.</p><p>This section discusses basic evaluation metrics commonly used for classification problems. If you are more interested in knowing how to <em>implement</em> a custom metric, please skip to <a href="/evaluation/metricbuild/">the next section</a>.</p><h2 id='defining-metric' class='header-anchors'>Defining Metric</h2><p>Metric evaluates the quality of an engine by comparing engine&#39;s output (predicted result) with the original label (actual result). A engine serving better prediction should yield a higher metric score, the tuning module returns the engine parameter with the highest score. It is sometimes called <a href="http://en.wikipedia.org/wiki/Loss_function"><em>loss function</em></a> in literature, where the goal is to minimize the loss function.</p><p>During tuning, it is important for us to understand the definition of the metric, to make sure it is aligned with the prediction en
 gine&#39;s goal.</p><p>In the classification template, we use <em>Accuracy</em> as our metric. <em>Accuracy</em> is defined as: the percentage of queries which the engine is able to predict the correct label.</p><h2 id='common-metrics' class='header-anchors'>Common Metrics</h2><p>We illustrate the choice of metric with the following confusion matrix. Row represents the engine predicted label, column represents the actual label. The second row means that of the 200 testing data points, the engine predicted 60 (15 + 35 + 10) of them as label 2.0, among which 35 are correct prediction (i.e. actual label is 2.0, matches with the prediction), and 25 are wrong.</p> <table><thead> <tr> <th style="text-align: center"></th> <th style="text-align: center">Actual = 1.0</th> <th style="text-align: center">Actual = 2.0</th> <th style="text-align: center">Actual = 3.0</th> </tr> </thead><tbody> <tr> <td style="text-align: center"><strong>Predicted = 1.0</strong></td> <td style="text-align: center
 ">30</td> <td style="text-align: center">0</td> <td style="text-align: center">60</td> </tr> <tr> <td style="text-align: center"><strong>Predicted = 2.0</strong></td> <td style="text-align: center">15</td> <td style="text-align: center">35</td> <td style="text-align: center">10</td> </tr> <tr> <td style="text-align: center"><strong>Predicted = 3.0</strong></td> <td style="text-align: center">0</td> <td style="text-align: center">0</td> <td style="text-align: center">50</td> </tr> </tbody></table> <h3 id='accuracy' class='header-anchors'>Accuracy</h3><p>Accuracy means that how many data points are predicted correctly. It is one of the simplest form of evaluation metrics. The accuracy score is # of correct points / # total = (30 + 35 + 50) / 200 = 0.575.</p><h3 id='precision' class='header-anchors'>Precision</h3><p>Precision is a metric for binary classifier which measures the correctness among all positive labels. A binary classifier gives only two output values (i.e. positive and ne
 gative). For problem where there are multiple values (3 in our example), we first have to transform our problem into a binary classification problem. For example, we can have problem whether label = 1.0. The confusion matrix now becomes:</p> <table><thead> <tr> <th style="text-align: center"></th> <th style="text-align: center">Actual = 1.0</th> <th style="text-align: center">Actual != 1.0</th> </tr> </thead><tbody> <tr> <td style="text-align: center"><strong>Predicted = 1.0</strong></td> <td style="text-align: center">30</td> <td style="text-align: center">60</td> </tr> <tr> <td style="text-align: center"><strong>Predicted != 1.0</strong></td> <td style="text-align: center">15</td> <td style="text-align: center">95</td> </tr> </tbody></table> <p>Precision is the ratio between the number of correct positive answer (true positive) and the sum of correct positive answer (true positive) and wrong but positively labeled answer (false positive). In this case, the precision is 30 / (30 + 
 60) = ~0.3333.</p><h3 id='recall' class='header-anchors'>Recall</h3><p>Recall is a metric for binary classifier which measures how many positive labels are successfully predicted amongst all positive labels. Formally, it is the ratio between the number of correct positive answer (true positive) and the sum of correct positive answer (true positive) and wrongly negatively labeled answer (false negative). In this case, the recall is 30 / (30 + 15) = ~0.6667.</p><p>As we have discussed several common metrics for classification problem, we can implement them using the <code>Metric</code> class in <a href="/evaluation/metricbuild">the next section</a>.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="//predictionio.apache.org/install/" target="blank">Download</a></li><li><a href="//predictionio.apache.org/" target="blank">D
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 a href="#defining-metric">Defining Metric</a> </li> <li> <a href="#common-metrics">Common Metrics</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/predictionio/tree/livedoc/docs/manual/source/evaluation/metricchoose.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="#">Tuning and Evaluation</a><span class="spacer">&gt;</span></li><li><span class="last">Choosing Evaluation Metrics</span></li></ul></div><div id="page-title"><h1>Choosing Evaluation Metrics</h1></div></div><div class="content"> <p>The <a href="/evaluation/paramtuning/">hyperparameter tuning module</a> allows us to select the optimal engine parameter defined by a <code>Metric</code>. <code>Metric</code> determines the quality of an engine variant. We have skimmed through the process of choosing the right <code>Metric</code> in previous secti
 ons.</p><p>This section discusses basic evaluation metrics commonly used for classification problems. If you are more interested in knowing how to <em>implement</em> a custom metric, please skip to <a href="/evaluation/metricbuild/">the next section</a>.</p><h2 id='defining-metric' class='header-anchors'>Defining Metric</h2><p>Metric evaluates the quality of an engine by comparing engine&#39;s output (predicted result) with the original label (actual result). A engine serving better prediction should yield a higher metric score, the tuning module returns the engine parameter with the highest score. It is sometimes called <a href="http://en.wikipedia.org/wiki/Loss_function"><em>loss function</em></a> in literature, where the goal is to minimize the loss function.</p><p>During tuning, it is important for us to understand the definition of the metric, to make sure it is aligned with the prediction engine&#39;s goal.</p><p>In the classification template, we use <em>Accuracy</em> as our 
 metric. <em>Accuracy</em> is defined as: the percentage of queries which the engine is able to predict the correct label.</p><h2 id='common-metrics' class='header-anchors'>Common Metrics</h2><p>We illustrate the choice of metric with the following confusion matrix. Row represents the engine predicted label, column represents the actual label. The second row means that of the 200 testing data points, the engine predicted 60 (15 + 35 + 10) of them as label 2.0, among which 35 are correct prediction (i.e. actual label is 2.0, matches with the prediction), and 25 are wrong.</p> <table><thead> <tr> <th style="text-align: center"></th> <th style="text-align: center">Actual = 1.0</th> <th style="text-align: center">Actual = 2.0</th> <th style="text-align: center">Actual = 3.0</th> </tr> </thead><tbody> <tr> <td style="text-align: center"><strong>Predicted = 1.0</strong></td> <td style="text-align: center">30</td> <td style="text-align: center">0</td> <td style="text-align: center">60</td> 
 </tr> <tr> <td style="text-align: center"><strong>Predicted = 2.0</strong></td> <td style="text-align: center">15</td> <td style="text-align: center">35</td> <td style="text-align: center">10</td> </tr> <tr> <td style="text-align: center"><strong>Predicted = 3.0</strong></td> <td style="text-align: center">0</td> <td style="text-align: center">0</td> <td style="text-align: center">50</td> </tr> </tbody></table> <h3 id='accuracy' class='header-anchors'>Accuracy</h3><p>Accuracy means that how many data points are predicted correctly. It is one of the simplest form of evaluation metrics. The accuracy score is # of correct points / # total = (30 + 35 + 50) / 200 = 0.575.</p><h3 id='precision' class='header-anchors'>Precision</h3><p>Precision is a metric for binary classifier which measures the correctness among all positive labels. A binary classifier gives only two output values (i.e. positive and negative). For problem where there are multiple values (3 in our example), we first have 
 to transform our problem into a binary classification problem. For example, we can have problem whether label = 1.0. The confusion matrix now becomes:</p> <table><thead> <tr> <th style="text-align: center"></th> <th style="text-align: center">Actual = 1.0</th> <th style="text-align: center">Actual != 1.0</th> </tr> </thead><tbody> <tr> <td style="text-align: center"><strong>Predicted = 1.0</strong></td> <td style="text-align: center">30</td> <td style="text-align: center">60</td> </tr> <tr> <td style="text-align: center"><strong>Predicted != 1.0</strong></td> <td style="text-align: center">15</td> <td style="text-align: center">95</td> </tr> </tbody></table> <p>Precision is the ratio between the number of correct positive answer (true positive) and the sum of correct positive answer (true positive) and wrong but positively labeled answer (false positive). In this case, the precision is 30 / (30 + 60) = ~0.3333.</p><h3 id='recall' class='header-anchors'>Recall</h3><p>Recall is a metr
 ic for binary classifier which measures how many positive labels are successfully predicted amongst all positive labels. Formally, it is the ratio between the number of correct positive answer (true positive) and the sum of correct positive answer (true positive) and wrongly negatively labeled answer (false negative). In this case, the recall is 30 / (30 + 15) = ~0.6667.</p><p>As we have discussed several common metrics for classification problem, we can implement them using the <code>Metric</code> class in <a href="/evaluation/metricbuild">the next section</a>.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="//predictionio.apache.org/install/" target="blank">Download</a></li><li><a href="//predictionio.apache.org/" target="blank">Docs</a></li><li><a href="//github.com/apache/predictionio" target="blank">GitHub</a></l
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-<!DOCTYPE html><html><head><title>Hyperparameter Tuning</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="Hyperparameter Tuning"/><link rel="canonical" href="https://predictionio.apache.org/evaluation/paramtuning/"/><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-eccfc6cb.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/la
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 ol-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO® Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO®</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</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="fina
 l" 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="/batchpredict/"><span>Batch Predictions</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><li class="level-2"><a class="final" href="/deploy/plugin/"><span>Engine Server Plugin</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</spa
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 gorithm</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>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 active" 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 Met
 rics</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>PredictionIO® Official Templates</span></a><ul><li class="level-2"><a class="final" href="/templates/"><span>Intro</span></a></li><li class="level-2"><a class="expandible" href="#"><span>Recommendation</span></a><ul><li class="level-3"><a class="final" href="/templates/recommendation/quickstart/"><span>Quick Start</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/dase/"><span>DASE</span></a></li><li class="level-3"><a class="final" href="/t
 emplates/recommendation/evaluation/"><span>Evaluation Explained</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/how-to/"><span>How-To</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/reading-custom-events/"><span>Read Custom Events</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/customize-data-prep/"><span>Customize Data Preparator</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/customize-serving/"><span>Customize Serving</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/training-with-implicit-preference/"><span>Train with Implicit Preference</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/blacklist-items/"><span>Filter Recommended Items by Blacklist in Query</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/batch-evaluator/"><span>Batch Pe
 rsistable Evaluator</span></a></li></ul></li><li class="level-2"><a class="expandible" href="#"><span>E-Commerce Recommendation</span></a><ul><li class="level-3"><a class="final" href="/templates/ecommercerecommendation/quickstart/"><span>Quick Start</span></a></li><li class="level-3"><a class="final" href="/templates/ecommercerecommendation/dase/"><span>DASE</span></a></li><li class="level-3"><a class="final" href="/templates/ecommercerecommendation/how-to/"><span>How-To</span></a></li><li class="level-3"><a class="final" href="/templates/ecommercerecommendation/train-with-rate-event/"><span>Train with Rate Event</span></a></li><li class="level-3"><a class="final" href="/templates/ecommercerecommendation/adjust-score/"><span>Adjust Score</span></a></li></ul></li><li class="level-2"><a class="expandible" href="#"><span>Similar Product</span></a><ul><li class="level-3"><a class="final" href="/templates/similarproduct/quickstart/"><span>Quick Start</span></a></li><li class="level-3"><
 a class="final" href="/templates/similarproduct/dase/"><span>DASE</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/how-to/"><span>How-To</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/multi-events-multi-algos/"><span>Multiple Events and Multiple Algorithms</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/return-item-properties/"><span>Returns Item Properties</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/train-with-rate-event/"><span>Train with Rate Event</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/rid-user-set-event/"><span>Get Rid of Events for Users</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/recommended-user/"><span>Recommend Users</span></a></li></ul></li><li class="level-2"><a class="expandible" href="#"><span>Classification</span></a><ul><li class="level-3
 "><a class="final" href="/templates/classification/quickstart/"><span>Quick Start</span></a></li><li class="level-3"><a class="final" href="/templates/classification/dase/"><span>DASE</span></a></li><li class="level-3"><a class="final" href="/templates/classification/how-to/"><span>How-To</span></a></li><li class="level-3"><a class="final" href="/templates/classification/add-algorithm/"><span>Use Alternative Algorithm</span></a></li><li class="level-3"><a class="final" href="/templates/classification/reading-custom-properties/"><span>Read Custom Properties</span></a></li></ul></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 Tutoria
 ls</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/"><s
 pan>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="/cli/"><span>Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/resources/release/"><span>Release Cadence</span></a></li><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><li class="level-1"><a class="expandible" href="#"><span>Apache Software Fo
 undation</span></a><ul><li class="level-2"><a class="final" href="https://www.apache.org/"><span>Apache Homepage</span></a></li><li class="level-2"><a class="final" href="https://www.apache.org/licenses/"><span>License</span></a></li><li class="level-2"><a class="final" href="https://www.apache.org/foundation/sponsorship.html"><span>Sponsorship</span></a></li><li class="level-2"><a class="final" href="https://www.apache.org/foundation/thanks.html"><span>Thanks</span></a></li><li class="level-2"><a class="final" href="https://www.apache.org/security/"><span>Security</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="#">Tuning and Evaluation</a><span class="spacer">&gt;</span></li><li><span class="last">Hyperparameter Tuning</span></li></ul></div><div id="page-title"><h1>Hyperparameter Tuning</h1></div></div><div id="table-of-content-wrapper"><h5>On
  this page</h5><aside id="table-of-contents"><ul> <li> <a href="#quick-start">Quick Start</a> </li> <li> <a href="#detailed-explanation">Detailed Explanation</a> </li> <li> <a href="#the-evaluation-design">The Evaluation Design</a> </li> <li> <a href="#evaluation-data-generation">Evaluation Data Generation</a> </li> <li> <a href="#evaluation-metrics">Evaluation Metrics</a> </li> <li> <a href="#parameters-generation">Parameters Generation</a> </li> <li> <a href="#running-the-evaluation">Running the Evaluation</a> </li> <li> <a href="#notes">Notes</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/predictionio/tree/livedoc/docs/manual/source/evaluation/paramtuning.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="#">Tuning and Evaluation</a><span class="spacer">&gt;</span></li><li><span class="last">Hyperp
 arameter Tuning</span></li></ul></div><div id="page-title"><h1>Hyperparameter Tuning</h1></div></div><div class="content"> <p>A PredictionIO engine is instantiated by a set of parameters. These parameters define which algorithm is to be used, as well supply the parameters for the algorithm itself. This naturally raises the question of how to choose the best set of parameters. The evaluation module streamlines the process of <em>tuning</em> the engine to the best parameter set and deploys it.</p><h2 id='quick-start' class='header-anchors'>Quick Start</h2><p>We demonstrate the evaluation with <a href="/templates/classification/quickstart/">the classification template</a>. The classification template uses a naive bayesian algorithm that has a smoothing parameter. We evaluate the prediction quality against different parameter values to find the best parameter values, and then deploy it.</p><h3 id='edit-the-appid' class='header-anchors'>Edit the AppId</h3><p>Edit MyClassification/src/mai
 n/scala/<strong><em>Evaluation.scala</em></strong> to specify the <em>appId</em> you used to import the data.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+<!DOCTYPE html><html><head><title>Hyperparameter Tuning</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="Hyperparameter Tuning"/><link rel="canonical" href="https://predictionio.apache.org/evaluation/paramtuning/"/><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-eccfc6cb.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/la
 test/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.apache.org/"><img alt="Apache PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a><span>®</span></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/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>Hyperparameter Tuning</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="c
 ol-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO® Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO®</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</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="fina
 l" 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="/community/projects/#sdks"><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="/batchpredict/"><span>Batch Predictions</span></a></li><li class="level-2"><a class="final" href="/deploy/monitorin
 g/"><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><li class="level-2"><a class="final" href="/deploy/plugin/"><span>Engine Server Plugin</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" href="/datacollection/"><span>Event Server Overview</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><li class="level-2"><a class="final" href="/datacollection/plugin/"><span>Event Server Plugin</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choo
 sing an Algorithm</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>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 active" 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 Eval
 uation 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>PredictionIO® Official Templates</span></a><ul><li class="level-2"><a class="final" href="/templates/"><span>Intro</span></a></li><li class="level-2"><a class="expandible" href="#"><span>Recommendation</span></a><ul><li class="level-3"><a class="final" href="/templates/recommendation/quickstart/"><span>Quick Start</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/dase/"><span>DASE</span></a></li><li class="level-3"><a class="final
 " href="/templates/recommendation/evaluation/"><span>Evaluation Explained</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/how-to/"><span>How-To</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/reading-custom-events/"><span>Read Custom Events</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/customize-data-prep/"><span>Customize Data Preparator</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/customize-serving/"><span>Customize Serving</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/training-with-implicit-preference/"><span>Train with Implicit Preference</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/blacklist-items/"><span>Filter Recommended Items by Blacklist in Query</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/batch-evaluator/"><spa
 n>Batch Persistable Evaluator</span></a></li></ul></li><li class="level-2"><a class="expandible" href="#"><span>E-Commerce Recommendation</span></a><ul><li class="level-3"><a class="final" href="/templates/ecommercerecommendation/quickstart/"><span>Quick Start</span></a></li><li class="level-3"><a class="final" href="/templates/ecommercerecommendation/dase/"><span>DASE</span></a></li><li class="level-3"><a class="final" href="/templates/ecommercerecommendation/how-to/"><span>How-To</span></a></li><li class="level-3"><a class="final" href="/templates/ecommercerecommendation/train-with-rate-event/"><span>Train with Rate Event</span></a></li><li class="level-3"><a class="final" href="/templates/ecommercerecommendation/adjust-score/"><span>Adjust Score</span></a></li></ul></li><li class="level-2"><a class="expandible" href="#"><span>Similar Product</span></a><ul><li class="level-3"><a class="final" href="/templates/similarproduct/quickstart/"><span>Quick Start</span></a></li><li class="
 level-3"><a class="final" href="/templates/similarproduct/dase/"><span>DASE</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/how-to/"><span>How-To</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/multi-events-multi-algos/"><span>Multiple Events and Multiple Algorithms</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/return-item-properties/"><span>Returns Item Properties</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/train-with-rate-event/"><span>Train with Rate Event</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/rid-user-set-event/"><span>Get Rid of Events for Users</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/recommended-user/"><span>Recommend Users</span></a></li></ul></li><li class="level-2"><a class="expandible" href="#"><span>Classification</span></a><ul><li clas
 s="level-3"><a class="final" href="/templates/classification/quickstart/"><span>Quick Start</span></a></li><li class="level-3"><a class="final" href="/templates/classification/dase/"><span>DASE</span></a></li><li class="level-3"><a class="final" href="/templates/classification/how-to/"><span>How-To</span></a></li><li class="level-3"><a class="final" href="/templates/classification/add-algorithm/"><span>Use Alternative Algorithm</span></a></li><li class="level-3"><a class="final" href="/templates/classification/reading-custom-properties/"><span>Read Custom Properties</span></a></li></ul></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>De
 mo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/community/projects/#demos"><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="expandibl
 e" 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="/cli/"><span>Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/resources/release/"><span>Release Cadence</span></a></li><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><li class="level-1"><a class="expandible" href="#"><span>Apache Software Foundation</span></a><ul><li class="level-2"><a class="final" href="https://www.apache.or
 g/"><span>Apache Homepage</span></a></li><li class="level-2"><a class="final" href="https://www.apache.org/licenses/"><span>License</span></a></li><li class="level-2"><a class="final" href="https://www.apache.org/foundation/sponsorship.html"><span>Sponsorship</span></a></li><li class="level-2"><a class="final" href="https://www.apache.org/foundation/thanks.html"><span>Thanks</span></a></li><li class="level-2"><a class="final" href="https://www.apache.org/security/"><span>Security</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="#">Tuning and Evaluation</a><span class="spacer">&gt;</span></li><li><span class="last">Hyperparameter Tuning</span></li></ul></div><div id="page-title"><h1>Hyperparameter Tuning</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#quick-start">Quick Sta
 rt</a> </li> <li> <a href="#detailed-explanation">Detailed Explanation</a> </li> <li> <a href="#the-evaluation-design">The Evaluation Design</a> </li> <li> <a href="#evaluation-data-generation">Evaluation Data Generation</a> </li> <li> <a href="#evaluation-metrics">Evaluation Metrics</a> </li> <li> <a href="#parameters-generation">Parameters Generation</a> </li> <li> <a href="#running-the-evaluation">Running the Evaluation</a> </li> <li> <a href="#notes">Notes</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/predictionio/tree/livedoc/docs/manual/source/evaluation/paramtuning.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="#">Tuning and Evaluation</a><span class="spacer">&gt;</span></li><li><span class="last">Hyperparameter Tuning</span></li></ul></div><div id="page-title"><h1>Hyperparameter Tuning</h
 1></div></div><div class="content"> <p>A PredictionIO engine is instantiated by a set of parameters. These parameters define which algorithm is to be used, as well supply the parameters for the algorithm itself. This naturally raises the question of how to choose the best set of parameters. The evaluation module streamlines the process of <em>tuning</em> the engine to the best parameter set and deploys it.</p><h2 id='quick-start' class='header-anchors'>Quick Start</h2><p>We demonstrate the evaluation with <a href="/templates/classification/quickstart/">the classification template</a>. The classification template uses a naive bayesian algorithm that has a smoothing parameter. We evaluate the prediction quality against different parameter values to find the best parameter values, and then deploy it.</p><h3 id='edit-the-appid' class='header-anchors'>Edit the AppId</h3><p>Edit MyClassification/src/main/scala/<strong><em>Evaluation.scala</em></strong> to specify the <em>appId</em> you us
 ed to import the data.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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