type_gpca.html

来自「一个由Mike Gashler完成的机器学习方面的includes neural」· HTML 代码 · 共 31 行

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<html><head><title>Generated Documentation</title></head><body>	<image src="headerimage.png">	<br><br><table><tr><td><big><big><big style="font-family: arial;"><b>GPCA</b></big></big></big><br><br></td><td> Principle Component Analysis</td></tr></table><br><br><big><big><i>Statics (public)</i></big></big><br><div style="margin-left: 40px;"><a href="type_GArffData.html">GArffData</a>* <big><b>DoPCA</b></big>(<a href="type_GArffRelation.html">GArffRelation</a>* pRelation, <a href="type_GArffData.html">GArffData</a>* pData)<br><div style="margin-left: 80px;"><font color=brown> Performs principle component analysis on the input dimensions of the data. It doesn't drop any dimensions, it just squishes the data into the first input dimensions. If you want to drop dimensions, just ignore the last several input dimensions. You are repsonsible to delete the data set this returns. Output dimensions are just copied straight across.</font></div><br>void <big><b>Test</b></big>()<br></div><br><big><big><i>Constructors (non-public)</i></big></big><br><div style="margin-left: 40px;"><big><b>GPCA</b></big>(<a href="type_GArffRelation.html">GArffRelation</a>* pRelation, <a href="type_GArffData.html">GArffData</a>* pData)<br></div><br><big><big><i>Destructors</i></big></big><br><div style="margin-left: 40px;"><big><b>~GPCA</b></big>()<br></div><br><big><big><i>Protected</i></big></big><br><div style="margin-left: 40px;">void <big><b>DoPCA</b></big>()<br><a href="type_GArffData.html">GArffData</a>* <big><b>DropOutputData</b></big>()<br></div><br></body></html>

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