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<p><a href="dbscan_8hpp_source.html">Go to the source code of this file.</a></p>
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Classes</h2></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class  </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1dbscan_1_1DBSCAN.html">mlpack::dbscan::DBSCAN< RangeSearchType, PointSelectionPolicy ></a></td></tr>
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<tr class="memdesc:"><td class="mdescLeft"> </td><td class="mdescRight"><a class="el" href="classmlpack_1_1dbscan_1_1DBSCAN.html" title="DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is a clustering technique descri...">DBSCAN</a> (Density-Based Spatial Clustering of Applications with Noise) is a clustering technique described in the following paper: <a href="classmlpack_1_1dbscan_1_1DBSCAN.html#details">More...</a><br /></td></tr>
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Namespaces</h2></td></tr>
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<tr class="memdesc:namespacemlpack"><td class="mdescLeft"> </td><td class="mdescRight">Linear algebra utility functions, generally performed on matrices or vectors. <br /></td></tr>
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<tr class="separator:"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:namespacemlpack_1_1dbscan"><td class="memItemLeft" align="right" valign="top">  </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacemlpack_1_1dbscan.html">mlpack::dbscan</a></td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
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<div class="textblock"><dl class="section author"><dt>Author</dt><dd>Ryan Curtin</dd></dl>
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<p>An implementation of the DBSCAN clustering method, which is flexible enough to support other algorithms for finding nearest neighbors. </p>
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<p>Definition in file <a class="el" href="dbscan_8hpp_source.html">dbscan.hpp</a>.</p>
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