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A C++ based data analytics platform for processing large-scale real-time streams containing structured and unstructured data

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<!doctype html> <html> <head> <meta name="generator" content="JSDoc 3"> <meta charset="utf-8"> <title>Class: ClassificationScore</title> <link rel="stylesheet" href="https://brick.a.ssl.fastly.net/Karla:400,400i,700,700i" type="text/css"> <link rel="stylesheet" href="https://brick.a.ssl.fastly.net/Noto+Serif:400,400i,700,700i" type="text/css"> <link rel="stylesheet" href="https://brick.a.ssl.fastly.net/Inconsolata:500" type="text/css"> <link href="css/baseline.css" rel="stylesheet"> </head> <body onload="prettyPrint()"> <nav id="jsdoc-navbar" role="navigation" class="jsdoc-navbar"> <div id="jsdoc-navbar-container"> <div id="jsdoc-navbar-content"> <a href="index.html" class="jsdoc-navbar-package-name">QMiner JavaScript API v9.4.0</a> </div> </div> </nav> <div id="jsdoc-body-container"> <div id="jsdoc-content"> <div id="jsdoc-content-container"> <div id="jsdoc-main" role="main"> <header class="page-header"> <div class="symbol-detail-labels"><span class="label label-kind">class</span>&nbsp;<span class="label label-static">static</span></div> <h1><small><a href="module-analytics.html">analytics</a>~<wbr><a href="module-analytics-metrics.html">metrics</a>.<wbr></small><span class="symbol-name">ClassificationScore</span></h1> <p class="source-link">Source: <a href="analyticsdoc.js.html#source-line-3431">analyticsdoc.<wbr>js:3431</a></p> <div class="symbol-classdesc"> <p>Class implements several classification measures (precision, recall, F1, accuracy).</p> </div> <dl class="dl-compact"> </dl> </header> <section id="summary"> <div class="summary-callout"> <h2 class="summary-callout-heading">Property</h2> <div class="summary-content"> <div class="summary-column"> <dl class="dl-summary-callout"> <dt><a href="module-analytics-metrics.ClassificationScore.html#scores">scores</a></dt> <dd> </dd> </dl> </div> <div class="summary-column"> </div> <div class="summary-column"> </div> </div> </div> <div class="summary-callout"> <h2 class="summary-callout-heading">Method</h2> <div class="summary-content"> <div class="summary-column"> <dl class="dl-summary-callout"> <dt><a href="module-analytics-metrics.ClassificationScore.html#push">push(correct, predicted)</a></dt> <dd> </dd> </dl> </div> <div class="summary-column"> </div> <div class="summary-column"> </div> </div> </div> </section> <section> <h2 id="ClassificationScore">new&nbsp;<span class="symbol-name">ClassificationScore</span><span class="signature"><span class="signature-params">(yTrue, yPred)</span></span></h2> <p>For evaluating provided categories from binary? classifiers.</p> <section> <h3>Parameters</h3> <table class="jsdoc-details-table"> <thead> <tr> <th>Name</th> <th>Type</th> <th>Optional</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td> <p>yTrue</p> </td> <td> <p>(Array of number or <a href="module-la.Vector.html">module:la.Vector</a>)</p> </td> <td> <p>&nbsp;</p> </td> <td> <p>Ground truth (correct) lable(s).</p> </td> </tr> <tr> <td> <p>yPred</p> </td> <td> <p>(Array of number or <a href="module-la.Vector.html">module:la.Vector</a>)</p> </td> <td> <p>&nbsp;</p> </td> <td> <p>Predicted (estimated) lable(s).</p> </td> </tr> </tbody> </table> </section> <dl class="dl-compact"> </dl> </section> <section> <h2>Property</h2> <section> <h3 id="scores"><span class="symbol-name">scores</span></h3> <p>Returns <code>Object</code> containing different classification measures.</p> <dl class="dl-compact"> <dt>Returns</dt> <dd> <p><code>Object</code>B scores - Object with different classification socres.</p> </dd> <dd> <p><code>number</code>B scores.count - Count.</p> </dd> <dd> <p><code>number</code>B scores.TP - Number of true positives.</p> </dd> <dd> <p><code>number</code>B scores.TN - Number of true negative.</p> </dd> <dd> <p><code>number</code>B scores.FP - Number of false positives.</p> </dd> <dd> <p><code>number</code>B scores.FN - Number of false positives.</p> </dd> <dd> <p><code>number</code>B scores.all - Number of all results.</p> </dd> <dd> <p><code>number</code>B scores.accuracy - Accuracy score. Formula: <code>(tp + tn) / (tp + fp + fn + tn)</code>.</p> </dd> <dd> <p><code>number</code>B scores.precision - Precision score. Formula: <code>tp / (tp + fp)</code>.</p> </dd> <dd> <p><code>number</code>B scores.recall - Recall score. Formula: <code>tp / (tp + fn)</code>.</p> </dd> <dd> <p><code>number</code>B scores.f1 - F1 score. Formula: <code>2 * (precision * recall) / (precision + recall)</code>.</p> </dd> </dl> </section> <h2>Method</h2> <section> <h3 id="push"><span class="symbol-name">push</span><span class="signature"><span class="signature-params">(correct, predicted)</span></span></h3> <p>Adds prediction to the current statistics. Labels can be either integers. or integer array (when there are zero or more then one lables).</p> <section> <h4>Parameters</h4> <table class="jsdoc-details-table"> <thead> <tr> <th>Name</th> <th>Type</th> <th>Optional</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td> <p>correct</p> </td> <td> <p>number</p> </td> <td> <p>&nbsp;</p> </td> <td> <p>Correct lable.</p> </td> </tr> <tr> <td> <p>predicted</p> </td> <td> <p>number</p> </td> <td> <p>&nbsp;</p> </td> <td> <p>Predicted lable.</p> </td> </tr> </tbody> </table> </section> <dl class="dl-compact"> </dl> </section> </section> </div> </div> <nav id="jsdoc-toc-nav" role="navigation"></nav> </div> </div> <footer id="jsdoc-footer" class="jsdoc-footer"> <div id="jsdoc-footer-container"> <p> </p> </div> </footer> <script src="scripts/jquery.min.js"></script> <script src="scripts/tree.jquery.js"></script> <script src="scripts/prettify.js"></script> <script src="scripts/jsdoc-toc.js"></script> <script src="scripts/linenumber.js"></script> <script src="scripts/scrollanchor.js"></script> </body> </html>