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 >class="spacer">&gt;</span></li><li><span 
 >class="last">Overview</span></li></ul></div><div id="page-title"><h1>Tuning 
 >and Evaluation</h1></div></div><div id="table-of-content-wrapper"><a 
 >id="edit-page-link" href="https://g
 
ithub.com/apache/predictionio/tree/livedoc/docs/manual/source/evaluation/index.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="#">ML Tuning and 
Evaluation</a><span class="spacer">&gt;</span></li><li><span 
class="last">Overview</span></li></ul></div><div id="page-title"><h1>Tuning and 
Evaluation</h1></div></div><div class="content"> <p>PredictionIO&#39;s 
evaluation module allows you to streamline the process of testing lots of knobs 
in engine parameters and deploy the best one out of it using statisically sound 
cross-validation methods.</p><p>There are two key components:</p><h3 
id='engine' class='header-anchors'>Engine</h3><p>It is our evaluation target. 
During evaluation, in addition to the <em>train</em> and <em>deploy</em> mode 
we describe in earlier sections, the engine also generates a list of testing 
data points. These data poin
 ts are a sequence of <em>Query</em> and <em>Actual Result</em> tuples. 
<em>Queries</em> are sent to the engine and the engine responds with a 
<em>Predicted Result</em>, in the same way as how the engine serves a 
query.</p><h3 id='evaluator' class='header-anchors'>Evaluator</h3><p>The 
evaluator joins the sequence of <em>Query</em>, <em>Predicted Result</em>, and 
<em>Actual Result</em> together and evaluates the quality of the engine. 
PredictionIO enables you to implement any metric with just a few lines of 
code.</p><p><img alt="PredictionIO Evaluation Overview" 
src="/images/engine-evaluation-4ab1bfeb.png"/></p><p>We will discuss various 
aspects of evaluation with PredictionIO.</p> <ul> <li><a 
href="/evaluation/paramtuning/">Hyperparameter Tuning</a> - it is an end-to-end 
example of using PredictionIO evaluation module to select and deploy the best 
engine parameter.</li> <li><a 
href="/evaluation/evaluationdashboard/">Evaluation Dashboard</a> - it is the 
dashboard where you can see a d
 etailed breakdown of all previous evaluations.</li> <li><a 
href="/evaluation/metricchoose/">Choosing Evaluation Metrics</a> - we cover 
some basic machine learning metrics</li> <li><a 
href="/evaluation/metricbuild/">Bulding Evaluation Metrics</a> - we illustrate 
how to implement a custom metric with as few as one line of code (plus some 
boilerplates).</li> </ul> </div></div></div></div><footer><div 
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class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web 
Service</span></a></li><li class="level-2"><a class="final" 
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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 
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href="/datacollection/plugin/"><span>Event Server 
Plugin</span></a></li></ul></li><li class="level-1"><a class="expandible" 
href="#"><span>Choosing 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 active" 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 c
 lass="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" 
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class="level-3"><a class="final" 
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class="final" 
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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 
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href="#">Tuning and Evaluation</a><span 
class="spacer">&gt;</span></li><li><span 
class="last">Overview</span></li></ul></div><div id="page-title"><h1>Tuning and 
Evaluation</h1></div></div><div id="table-of-content-wrapper"><a 
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class="hidden-sm hidden xs"><ul><li><a href="#">Tuning and Evaluation</a><span 
class="spacer">&gt;</span></li><li><span 
class="last">Overview</span></li></ul></div><div id="page-title"><h1>Tuning and 
Evaluation</h1></div></div><div class="content"> <p>PredictionIO&#39;s 
evaluation module allows you to streamline the process of testing lots of knobs 
in engine parameters and deploy the best one out of it using statisically sound 
cross-validation methods.</p><p>There are two key components:</p><h3 
id='engine' class='header-anchors'>Engine</h3><p>It is our evaluation target. 
During evaluation, in addition to the <em>train</em> and <em>deploy</em> mode 
we describe in earlier sections, the engine also generates a list of testing 
data points. These data points are a 
 sequence of <em>Query</em> and <em>Actual Result</em> tuples. <em>Queries</em> 
are sent to the engine and the engine responds with a <em>Predicted 
Result</em>, in the same way as how the engine serves a query.</p><h3 
id='evaluator' class='header-anchors'>Evaluator</h3><p>The evaluator joins the 
sequence of <em>Query</em>, <em>Predicted Result</em>, and <em>Actual 
Result</em> together and evaluates the quality of the engine. PredictionIO 
enables you to implement any metric with just a few lines of code.</p><p><img 
alt="PredictionIO Evaluation Overview" 
src="/images/engine-evaluation-4ab1bfeb.png"/></p><p>We will discuss various 
aspects of evaluation with PredictionIO.</p> <ul> <li><a 
href="/evaluation/paramtuning/">Hyperparameter Tuning</a> - it is an end-to-end 
example of using PredictionIO evaluation module to select and deploy the best 
engine parameter.</li> <li><a 
href="/evaluation/evaluationdashboard/">Evaluation Dashboard</a> - it is the 
dashboard where you can see a detailed b
 reakdown of all previous evaluations.</li> <li><a 
href="/evaluation/metricchoose/">Choosing Evaluation Metrics</a> - we cover 
some basic machine learning metrics</li> <li><a 
href="/evaluation/metricbuild/">Bulding Evaluation Metrics</a> - we illustrate 
how to implement a custom metric with as few as one line of code (plus some 
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