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| 15 | <h1>work/mixpp/libBM.h File Reference</h1>Bayesian Models (bm) that use Bayes rule to learn from observations. <a href="#_details">More...</a> |
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| 16 | <p> |
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| 17 | <code>#include <itpp/itbase.h></code><br> |
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| 18 | |
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| 19 | <p> |
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| 20 | <a href="libBM_8h-source.html">Go to the source code of this file.</a><table border="0" cellpadding="0" cellspacing="0"> |
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| 21 | <tr><td></td></tr> |
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| 22 | <tr><td colspan="2"><br><h2>Classes</h2></td></tr> |
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| 23 | <tr><td class="memItemLeft" nowrap align="right" valign="top">class </td><td class="memItemRight" valign="bottom"><a class="el" href="classRV.html">RV</a></td></tr> |
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| 24 | |
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| 25 | <tr><td class="mdescLeft"> </td><td class="mdescRight">Class representing variables, most often random variables. <a href="classRV.html#_details">More...</a><br></td></tr> |
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| 27 | |
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| 28 | <tr><td class="mdescLeft"> </td><td class="mdescRight">Class representing function of variables. <a href="classfnc.html#_details">More...</a><br></td></tr> |
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| 29 | <tr><td class="memItemLeft" nowrap align="right" valign="top">class </td><td class="memItemRight" valign="bottom"><a class="el" href="classBM.html">BM</a></td></tr> |
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| 30 | |
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| 31 | <tr><td class="mdescLeft"> </td><td class="mdescRight">Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities. <a href="classBM.html#_details">More...</a><br></td></tr> |
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| 32 | <tr><td class="memItemLeft" nowrap align="right" valign="top">class </td><td class="memItemRight" valign="bottom"><a class="el" href="classepdf.html">epdf</a></td></tr> |
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| 33 | |
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| 34 | <tr><td class="mdescLeft"> </td><td class="mdescRight">Probability density function with numerical statistics, e.g. posterior density. <a href="classepdf.html#_details">More...</a><br></td></tr> |
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| 36 | |
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| 37 | <tr><td class="mdescLeft"> </td><td class="mdescRight">Conditional probability density, e.g. modeling some dependencies. <a href="classmpdf.html#_details">More...</a><br></td></tr> |
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| 38 | </table> |
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| 39 | <hr><a name="_details"></a><h2>Detailed Description</h2> |
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| 40 | Bayesian Models (bm) that use Bayes rule to learn from observations. |
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| 41 | <p> |
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| 42 | <dl class="author" compact><dt><b>Author:</b></dt><dd>Vaclav Smidl.</dd></dl> |
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| 43 | ----------------------------------- BDM++ - C++ library for Bayesian Decision Making under Uncertainty<p> |
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| 44 | Using IT++ for numerical operations ----------------------------------- <hr size="1"><address style="text-align: right;"><small>Generated on Sun Jan 20 12:47:33 2008 for mixpp by |
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