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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 
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 >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 
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 >href="/datacollection/batchimport/"><span>Importing Data in 
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class="level-3"><a class="final" 
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Serving</span></a></li><li class="level-3"><a class="final" 
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 able Evaluator</span></a></li></ul></li><li class="level-2"><a 
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Properties</span></a></li><li class="level-3"><a class="final" 
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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" 
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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" 
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Properties</span></a></li></ul></li></ul></li><li class="level-1"><a 
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hidden-lg"><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>ML Tuning 
and Evaluation</h1></div></div><div id="table-of-content-wrapper"><a 
id="edit-page-l
 ink" 
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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>ML 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 tes
 ting 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 th
 e dashboard where you can see a detailed 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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href="#"><span>Collecting and Analyzing Data</span></a><u
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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 
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Tools</span></a></li><li class="level-2"><a class="final" 
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Plugin</span></a></li></ul></li><li class="level-1"><a class="expandible" 
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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 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" 
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class="last">Overview</span></li></ul></div><div id="page-title"><h1>ML 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 
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engine parameter.</li> <li><a 
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Metrics</a> - we cover some basic machine learning metrics</li> <li><a 
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