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[48/51] [partial] incubator-madlib-site git commit: Add all files
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+ <div id="projectbrief">User Documentation for MADlib</div>
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+</script>
+<div id="doc-content">
+<!-- window showing the filter options -->
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+ onmouseover="return searchBox.OnSearchSelectShow()"
+ onmouseout="return searchBox.OnSearchSelectHide()"
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+ name="MSearchResults" id="MSearchResults">
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+</div>
+
+<div class="header">
+ <div class="summary">
+<a href="#func-members">Functions</a> </div>
+ <div class="headertitle">
+<div class="title">bayes.sql_in File Reference</div> </div>
+</div><!--header-->
+<div class="contents">
+
+<p>SQL functions for naive Bayes.
+<a href="#details">More...</a></p>
+<table class="memberdecls">
+<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a>
+Functions</h2></td></tr>
+<tr class="memitem:a0671e6ac35a1967f41d2efb9e8417e1b"><td class="memItemLeft" align="right" valign="top">args_and_value_double </td><td class="memItemRight" valign="bottom"><a class="el" href="bayes_8sql__in.html#a0671e6ac35a1967f41d2efb9e8417e1b">argmax_transition</a> (args_and_value_double oldmax, integer newkey, float8 newvalue)</td></tr>
+<tr class="separator:a0671e6ac35a1967f41d2efb9e8417e1b"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:ab150442ec577f4a0a3948176baf5ebd0"><td class="memItemLeft" align="right" valign="top">args_and_value_double </td><td class="memItemRight" valign="bottom"><a class="el" href="bayes_8sql__in.html#ab150442ec577f4a0a3948176baf5ebd0">argmax_combine</a> (args_and_value_double max1, args_and_value_double max2)</td></tr>
+<tr class="separator:ab150442ec577f4a0a3948176baf5ebd0"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:aa7017323fd6fad40c9acbbee5f1fec7e"><td class="memItemLeft" align="right" valign="top">integer[] </td><td class="memItemRight" valign="bottom"><a class="el" href="bayes_8sql__in.html#aa7017323fd6fad40c9acbbee5f1fec7e">argmax_final</a> (args_and_value_double finalstate)</td></tr>
+<tr class="separator:aa7017323fd6fad40c9acbbee5f1fec7e"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:ad47c68a2b8aeedf66d509f0c32a9732d"><td class="memItemLeft" align="right" valign="top">aggregate integer[] </td><td class="memItemRight" valign="bottom"><a class="el" href="bayes_8sql__in.html#ad47c68a2b8aeedf66d509f0c32a9732d">argmax</a> (integer key, float8 value)</td></tr>
+<tr class="separator:ad47c68a2b8aeedf66d509f0c32a9732d"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:aeb4eae7843dd789cc38d5fc57f4ccfb2"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="bayes_8sql__in.html#aeb4eae7843dd789cc38d5fc57f4ccfb2">create_nb_prepared_data_tables</a> (varchar trainingSource, varchar trainingClassColumn, varchar trainingAttrColumn, integer numAttrs, varchar featureProbsDestName, varchar classPriorsDestName)</td></tr>
+<tr class="memdesc:aeb4eae7843dd789cc38d5fc57f4ccfb2"><td class="mdescLeft"> </td><td class="mdescRight">Precompute all class priors and feature probabilities. <a href="#aeb4eae7843dd789cc38d5fc57f4ccfb2">More...</a><br /></td></tr>
+<tr class="separator:aeb4eae7843dd789cc38d5fc57f4ccfb2"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a3ed5ddbc4cab1013db8604be58a6da3d"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="bayes_8sql__in.html#a3ed5ddbc4cab1013db8604be58a6da3d">create_nb_prepared_data_tables</a> (varchar trainingSource, varchar trainingClassColumn, varchar trainingAttrColumn, varchar numericAttrsColumnIndices, integer numAttrs, varchar featureProbsDestName, varchar numericFeatureStatsDestName, varchar classPriorsDestName)</td></tr>
+<tr class="separator:a3ed5ddbc4cab1013db8604be58a6da3d"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a798402280fc6db710957ae3ab58767e0"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="bayes_8sql__in.html#a798402280fc6db710957ae3ab58767e0">create_nb_classify_view</a> (varchar featureProbsSource, varchar classPriorsSource, varchar classifySource, varchar classifyKeyColumn, varchar classifyAttrColumn, integer numAttrs, varchar destName)</td></tr>
+<tr class="memdesc:a798402280fc6db710957ae3ab58767e0"><td class="mdescLeft"> </td><td class="mdescRight">Create a view with columns <code>(key, nb_classification)</code> <a href="#a798402280fc6db710957ae3ab58767e0">More...</a><br /></td></tr>
+<tr class="separator:a798402280fc6db710957ae3ab58767e0"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a4e8e24120269be2b58f959ab5473b2cb"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="bayes_8sql__in.html#a4e8e24120269be2b58f959ab5473b2cb">create_nb_classify_view</a> (varchar featureProbsSource, varchar classPriorsSource, varchar classifySource, varchar classifyKeyColumn, varchar classifyAttrColumn, integer numAttrs, varchar numericFeatureStatsSource, varchar destName)</td></tr>
+<tr class="separator:a4e8e24120269be2b58f959ab5473b2cb"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a6472f620099368cb8c334e0badb12133"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="bayes_8sql__in.html#a6472f620099368cb8c334e0badb12133">create_nb_classify_view</a> (varchar trainingSource, varchar trainingClassColumn, varchar trainingAttrColumn, varchar classifySource, varchar classifyKeyColumn, varchar classifyAttrColumn, integer numAttrs, varchar destName)</td></tr>
+<tr class="separator:a6472f620099368cb8c334e0badb12133"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a76a03f1d7ff2b1891cb310668077b386"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="bayes_8sql__in.html#a76a03f1d7ff2b1891cb310668077b386">create_nb_classify_view</a> (varchar trainingSource, varchar trainingClassColumn, varchar trainingAttrColumn, varchar numericAttrsColumnIndices, varchar classifySource, varchar classifyKeyColumn, varchar classifyAttrColumn, integer numAttrs, varchar destName)</td></tr>
+<tr class="separator:a76a03f1d7ff2b1891cb310668077b386"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a163afffd0c845d325f060f74bcf02243"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="bayes_8sql__in.html#a163afffd0c845d325f060f74bcf02243">create_nb_probs_view</a> (varchar featureProbsSource, varchar classPriorsSource, varchar classifySource, varchar classifyKeyColumn, varchar classifyAttrColumn, integer numAttrs, varchar destName)</td></tr>
+<tr class="memdesc:a163afffd0c845d325f060f74bcf02243"><td class="mdescLeft"> </td><td class="mdescRight">Create view with columns <code>(key, class, nb_prob)</code> <a href="#a163afffd0c845d325f060f74bcf02243">More...</a><br /></td></tr>
+<tr class="separator:a163afffd0c845d325f060f74bcf02243"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a2e02b0ebb0b4c2ca77b1748662bae78f"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="bayes_8sql__in.html#a2e02b0ebb0b4c2ca77b1748662bae78f">create_nb_probs_view</a> (varchar featureProbsSource, varchar classPriorsSource, varchar classifySource, varchar classifyKeyColumn, varchar classifyAttrColumn, integer numAttrs, varchar numericFeatureStatsSource, varchar destName)</td></tr>
+<tr class="separator:a2e02b0ebb0b4c2ca77b1748662bae78f"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:aba5d695641530e55b25c8007b77142b9"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="bayes_8sql__in.html#aba5d695641530e55b25c8007b77142b9">create_nb_probs_view</a> (varchar trainingSource, varchar trainingClassColumn, varchar trainingAttrColumn, varchar classifySource, varchar classifyKeyColumn, varchar classifyAttrColumn, integer numAttrs, varchar destName)</td></tr>
+<tr class="separator:aba5d695641530e55b25c8007b77142b9"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a6d1186aa04f4d4e3ac44035467818d3c"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="bayes_8sql__in.html#a6d1186aa04f4d4e3ac44035467818d3c">create_nb_probs_view</a> (varchar trainingSource, varchar trainingClassColumn, varchar trainingAttrColumn, varchar numericAttrsColumnIndices, varchar classifySource, varchar classifyKeyColumn, varchar classifyAttrColumn, integer numAttrs, varchar destName)</td></tr>
+<tr class="separator:a6d1186aa04f4d4e3ac44035467818d3c"><td class="memSeparator" colspan="2"> </td></tr>
+</table>
+<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
+<div class="textblock"><dl class="section date"><dt>Date</dt><dd>January 2011</dd></dl>
+<dl class="section see"><dt>See also</dt><dd>For a brief introduction to Naive Bayes Classification, see the module description <a class="el" href="group__grp__bayes.html">Naive Bayes Classification</a>. </dd></dl>
+</div><h2 class="groupheader">Function Documentation</h2>
+<a class="anchor" id="ad47c68a2b8aeedf66d509f0c32a9732d"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">aggregate integer [] argmax </td>
+ <td>(</td>
+ <td class="paramtype">integer </td>
+ <td class="paramname"><em>key</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">float8 </td>
+ <td class="paramname"><em>value</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+
+</div>
+</div>
+<a class="anchor" id="ab150442ec577f4a0a3948176baf5ebd0"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">args_and_value_double argmax_combine </td>
+ <td>(</td>
+ <td class="paramtype">args_and_value_double </td>
+ <td class="paramname"><em>max1</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">args_and_value_double </td>
+ <td class="paramname"><em>max2</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+
+</div>
+</div>
+<a class="anchor" id="aa7017323fd6fad40c9acbbee5f1fec7e"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">integer [] argmax_final </td>
+ <td>(</td>
+ <td class="paramtype">args_and_value_double </td>
+ <td class="paramname"><em>finalstate</em></td><td>)</td>
+ <td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+
+</div>
+</div>
+<a class="anchor" id="a0671e6ac35a1967f41d2efb9e8417e1b"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">args_and_value_double argmax_transition </td>
+ <td>(</td>
+ <td class="paramtype">args_and_value_double </td>
+ <td class="paramname"><em>oldmax</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">integer </td>
+ <td class="paramname"><em>newkey</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">float8 </td>
+ <td class="paramname"><em>newvalue</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+
+</div>
+</div>
+<a class="anchor" id="a798402280fc6db710957ae3ab58767e0"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">void create_nb_classify_view </td>
+ <td>(</td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>featureProbsSource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classPriorsSource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifySource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifyKeyColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifyAttrColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">integer </td>
+ <td class="paramname"><em>numAttrs</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>destName</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+<p>The created relation will be</p>
+<p><code>{TABLE|VIEW} <em>destName</em> (key, nb_classification)</code></p>
+<p>where <code>nb_classification</code> is an array containing the most likely class(es) of the record in <em>classifySource</em> identified by <code>key</code>.</p>
+<dl class="params"><dt>Parameters</dt><dd>
+ <table class="params">
+ <tr><td class="paramname">featureProbsSource</td><td>Name of table with precomputed feature probabilities, as created with <a class="el" href="bayes_8sql__in.html#aeb4eae7843dd789cc38d5fc57f4ccfb2" title="Precompute all class priors and feature probabilities. ">create_nb_prepared_data_tables()</a> </td></tr>
+ <tr><td class="paramname">classPriorsSource</td><td>Name of table with precomputed class priors, as created with <a class="el" href="bayes_8sql__in.html#aeb4eae7843dd789cc38d5fc57f4ccfb2" title="Precompute all class priors and feature probabilities. ">create_nb_prepared_data_tables()</a> </td></tr>
+ <tr><td class="paramname">classifySource</td><td>Name of the relation that contains data to be classified </td></tr>
+ <tr><td class="paramname">classifyKeyColumn</td><td>Name of column in <em>classifySource</em> that can serve as unique identifier (the key of the source relation) </td></tr>
+ <tr><td class="paramname">classifyAttrColumn</td><td>Name of attributes-array column in <em>classifySource</em> </td></tr>
+ <tr><td class="paramname">numAttrs</td><td>Number of attributes to use for classification </td></tr>
+ <tr><td class="paramname">destName</td><td>Name of the view to create</td></tr>
+ </table>
+ </dd>
+</dl>
+<dl class="section note"><dt>Note</dt><dd><code>create_nb_classify_view</code> can be called in an ad-hoc fashion. See <a class="el" href="group__grp__bayes.html">Naive Bayes Classification</a> for instructions.</dd></dl>
+<dl class="section user"><dt>Usage</dt><dd><ol type="1">
+<li>Create Naive Bayes classifications view: <pre>SELECT <a class="el" href="bayes_8sql__in.html#a76a03f1d7ff2b1891cb310668077b386">create_nb_classify_view</a>(
+ '<em>featureProbsName</em>', '<em>classPriorsName</em>',
+ '<em>classifySource</em>', '<em>classifyKeyColumn</em>', '<em>classifyAttrColumn</em>',
+ <em>numAttrs</em>, '<em>destName</em>'
+);</pre></li>
+<li>Show Naive Bayes classifications: <pre>SELECT * FROM <em>destName</em>;</pre> </li>
+</ol>
+</dd></dl>
+
+</div>
+</div>
+<a class="anchor" id="a4e8e24120269be2b58f959ab5473b2cb"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">void create_nb_classify_view </td>
+ <td>(</td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>featureProbsSource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classPriorsSource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifySource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifyKeyColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifyAttrColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">integer </td>
+ <td class="paramname"><em>numAttrs</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>numericFeatureStatsSource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>destName</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+
+</div>
+</div>
+<a class="anchor" id="a6472f620099368cb8c334e0badb12133"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">void create_nb_classify_view </td>
+ <td>(</td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingSource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingClassColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingAttrColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifySource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifyKeyColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifyAttrColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">integer </td>
+ <td class="paramname"><em>numAttrs</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>destName</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+
+</div>
+</div>
+<a class="anchor" id="a76a03f1d7ff2b1891cb310668077b386"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">void create_nb_classify_view </td>
+ <td>(</td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingSource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingClassColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingAttrColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>numericAttrsColumnIndices</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifySource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifyKeyColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifyAttrColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">integer </td>
+ <td class="paramname"><em>numAttrs</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>destName</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+
+</div>
+</div>
+<a class="anchor" id="aeb4eae7843dd789cc38d5fc57f4ccfb2"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">void create_nb_prepared_data_tables </td>
+ <td>(</td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingSource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingClassColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingAttrColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">integer </td>
+ <td class="paramname"><em>numAttrs</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>featureProbsDestName</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classPriorsDestName</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+<p>Feature probabilities are stored in a table of format </p><pre>TABLE <em>featureProbsDestName</em> (
+ class INTEGER,
+ attr INTEGER,
+ value INTEGER,
+ cnt INTEGER,
+ attr_cnt INTEGER
+)</pre><p>Class priors are stored in a table of format </p><pre>TABLE <em>classPriorsDestName</em> (
+ class INTEGER,
+ class_cnt INTEGER,
+ all_cnt INTEGER
+)</pre><dl class="params"><dt>Parameters</dt><dd>
+ <table class="params">
+ <tr><td class="paramname">trainingSource</td><td>Name of relation containing the training data </td></tr>
+ <tr><td class="paramname">trainingClassColumn</td><td>Name of class column in training data </td></tr>
+ <tr><td class="paramname">trainingAttrColumn</td><td>Name of attributes-array column in training data </td></tr>
+ <tr><td class="paramname">numAttrs</td><td>Number of attributes to use for classification </td></tr>
+ <tr><td class="paramname">featureProbsDestName</td><td>Name of feature-probabilities table to create </td></tr>
+ <tr><td class="paramname">classPriorsDestName</td><td>Name of class-priors table to create</td></tr>
+ </table>
+ </dd>
+</dl>
+<dl class="section user"><dt>Usage</dt><dd>Precompute feature probabilities and class priors: <pre>SELECT <a class="el" href="bayes_8sql__in.html#a3ed5ddbc4cab1013db8604be58a6da3d">create_nb_prepared_data_tables</a>(
+ '<em>trainingSource</em>', '<em>trainingClassColumn</em>', '<em>trainingAttrColumn</em>',
+ <em>numAttrs</em>, '<em>featureProbsName</em>', '<em>classPriorsName</em>'
+);</pre> </dd></dl>
+
+</div>
+</div>
+<a class="anchor" id="a3ed5ddbc4cab1013db8604be58a6da3d"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">void create_nb_prepared_data_tables </td>
+ <td>(</td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingSource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingClassColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingAttrColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>numericAttrsColumnIndices</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">integer </td>
+ <td class="paramname"><em>numAttrs</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>featureProbsDestName</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>numericFeatureStatsDestName</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classPriorsDestName</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+
+</div>
+</div>
+<a class="anchor" id="a163afffd0c845d325f060f74bcf02243"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">void create_nb_probs_view </td>
+ <td>(</td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>featureProbsSource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classPriorsSource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifySource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifyKeyColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifyAttrColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">integer </td>
+ <td class="paramname"><em>numAttrs</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>destName</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+<p>The created view will be of the following form:</p>
+<pre>VIEW <em>destName</em> (
+ key ANYTYPE,
+ class INTEGER,
+ nb_prob FLOAT8
+)</pre><p>where <code>nb_prob</code> is the Naive-Bayes probability that <code>class</code> is the true class of the record in <em>classifySource</em> identified by <code>key</code>.</p>
+<dl class="params"><dt>Parameters</dt><dd>
+ <table class="params">
+ <tr><td class="paramname">featureProbsSource</td><td>Name of table with precomputed feature probabilities, as created with <a class="el" href="bayes_8sql__in.html#aeb4eae7843dd789cc38d5fc57f4ccfb2" title="Precompute all class priors and feature probabilities. ">create_nb_prepared_data_tables()</a> </td></tr>
+ <tr><td class="paramname">classPriorsSource</td><td>Name of table with precomputed class priors, as created with <a class="el" href="bayes_8sql__in.html#aeb4eae7843dd789cc38d5fc57f4ccfb2" title="Precompute all class priors and feature probabilities. ">create_nb_prepared_data_tables()</a> </td></tr>
+ <tr><td class="paramname">classifySource</td><td>Name of the relation that contains data to be classified </td></tr>
+ <tr><td class="paramname">classifyKeyColumn</td><td>Name of column in <em>classifySource</em> that can serve as unique identifier (the key of the source relation) </td></tr>
+ <tr><td class="paramname">classifyAttrColumn</td><td>Name of attributes-array column in <em>classifySource</em> </td></tr>
+ <tr><td class="paramname">numAttrs</td><td>Number of attributes to use for classification </td></tr>
+ <tr><td class="paramname">destName</td><td>Name of the view to create</td></tr>
+ </table>
+ </dd>
+</dl>
+<dl class="section note"><dt>Note</dt><dd><code>create_nb_probs_view</code> can be called in an ad-hoc fashion. See <a class="el" href="group__grp__bayes.html">Naive Bayes Classification</a> for instructions.</dd></dl>
+<dl class="section user"><dt>Usage</dt><dd><ol type="1">
+<li>Create Naive Bayes probabilities view: <pre>SELECT <a class="el" href="bayes_8sql__in.html#a6d1186aa04f4d4e3ac44035467818d3c">create_nb_probs_view</a>(
+ '<em>featureProbsName</em>', '<em>classPriorsName</em>',
+ '<em>classifySource</em>', '<em>classifyKeyColumn</em>', '<em>classifyAttrColumn</em>',
+ <em>numAttrs</em>, '<em>destName</em>'
+);</pre></li>
+<li>Show Naive Bayes probabilities: <pre>SELECT * FROM <em>destName</em>;</pre> </li>
+</ol>
+</dd></dl>
+
+</div>
+</div>
+<a class="anchor" id="a2e02b0ebb0b4c2ca77b1748662bae78f"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">void create_nb_probs_view </td>
+ <td>(</td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>featureProbsSource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classPriorsSource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifySource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifyKeyColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifyAttrColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">integer </td>
+ <td class="paramname"><em>numAttrs</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>numericFeatureStatsSource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>destName</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+
+</div>
+</div>
+<a class="anchor" id="aba5d695641530e55b25c8007b77142b9"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">void create_nb_probs_view </td>
+ <td>(</td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingSource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingClassColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingAttrColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifySource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifyKeyColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifyAttrColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">integer </td>
+ <td class="paramname"><em>numAttrs</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>destName</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+
+</div>
+</div>
+<a class="anchor" id="a6d1186aa04f4d4e3ac44035467818d3c"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">void create_nb_probs_view </td>
+ <td>(</td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingSource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingClassColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>trainingAttrColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>numericAttrsColumnIndices</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifySource</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifyKeyColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>classifyAttrColumn</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">integer </td>
+ <td class="paramname"><em>numAttrs</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">varchar </td>
+ <td class="paramname"><em>destName</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+
+</div>
+</div>
+</div><!-- contents -->
+</div><!-- doc-content -->
+<!-- start footer part -->
+<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
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+ <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.html">src</a></li><li class="navelem"><a class="el" href="dir_efbcf68973d247bbf15f9eecae7f24e3.html">ports</a></li><li class="navelem"><a class="el" href="dir_a4a48839224ef8488facbffa8a397967.html">postgres</a></li><li class="navelem"><a class="el" href="dir_dc596537ad427a4d866006d1a3e1fe29.html">modules</a></li><li class="navelem"><a class="el" href="dir_3ee26ceeadb429f807bd6cd822eca1b9.html">bayes</a></li><li class="navelem"><a class="el" href="bayes_8sql__in.html">bayes.sql_in</a></li>
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+ <td style="padding-left: 0.5em;">
+ <div id="projectname">
+ <span id="projectnumber">1.8</span>
+ </div>
+ <div id="projectbrief">User Documentation for MADlib</div>
+ </td>
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+ name="MSearchResults" id="MSearchResults">
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+
+<div class="header">
+ <div class="summary">
+<a href="#func-members">Functions</a> </div>
+ <div class="headertitle">
+<div class="title">c45.sql_in File Reference</div> </div>
+</div><!--header-->
+<div class="contents">
+
+<p>C4.5 APIs and main controller written in PL/PGSQL.
+<a href="#details">More...</a></p>
+<table class="memberdecls">
+<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a>
+Functions</h2></td></tr>
+<tr class="memitem:a4fbee855d22101d15d195d573189eb98"><td class="memItemLeft" align="right" valign="top">c45_train_result </td><td class="memItemRight" valign="bottom"><a class="el" href="c45_8sql__in.html#a4fbee855d22101d15d195d573189eb98">c45_train</a> (text split_criterion, text training_table_name, text result_tree_table_name, text validation_table_name, text continuous_feature_names, text feature_col_names, text id_col_name, text class_col_name, float confidence_level, text how2handle_missing_value, int max_tree_depth, float node_prune_threshold, float node_split_threshold, int verbosity)</td></tr>
+<tr class="memdesc:a4fbee855d22101d15d195d573189eb98"><td class="mdescLeft"> </td><td class="mdescRight">This is the long form API of training tree with all specified parameters. <a href="#a4fbee855d22101d15d195d573189eb98">More...</a><br /></td></tr>
+<tr class="separator:a4fbee855d22101d15d195d573189eb98"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a6c039416b94686b915e2a4c1133a5d44"><td class="memItemLeft" align="right" valign="top">c45_train_result </td><td class="memItemRight" valign="bottom"><a class="el" href="c45_8sql__in.html#a6c039416b94686b915e2a4c1133a5d44">c45_train</a> (text split_criterion, text training_table_name, text result_tree_table_name, text validation_table_name, text continuous_feature_names, text feature_col_names, text id_col_name, text class_col_name, float confidence_level, text how2handle_missing_value)</td></tr>
+<tr class="memdesc:a6c039416b94686b915e2a4c1133a5d44"><td class="mdescLeft"> </td><td class="mdescRight">C45 train algorithm in short form. <a href="#a6c039416b94686b915e2a4c1133a5d44">More...</a><br /></td></tr>
+<tr class="separator:a6c039416b94686b915e2a4c1133a5d44"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a18b30ff1a063e7cd16274bf7ab2a71dc"><td class="memItemLeft" align="right" valign="top">c45_train_result </td><td class="memItemRight" valign="bottom"><a class="el" href="c45_8sql__in.html#a18b30ff1a063e7cd16274bf7ab2a71dc">c45_train</a> (text split_criterion, text training_table_name, text result_tree_table_name)</td></tr>
+<tr class="memdesc:a18b30ff1a063e7cd16274bf7ab2a71dc"><td class="mdescLeft"> </td><td class="mdescRight">C45 train algorithm in short form. <a href="#a18b30ff1a063e7cd16274bf7ab2a71dc">More...</a><br /></td></tr>
+<tr class="separator:a18b30ff1a063e7cd16274bf7ab2a71dc"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:ac71787c47795b3b0b133cdbd37438242"><td class="memItemLeft" align="right" valign="top">set< text > </td><td class="memItemRight" valign="bottom"><a class="el" href="c45_8sql__in.html#ac71787c47795b3b0b133cdbd37438242">c45_genrule</a> (text tree_table_name, int verbosity)</td></tr>
+<tr class="memdesc:ac71787c47795b3b0b133cdbd37438242"><td class="mdescLeft"> </td><td class="mdescRight">Display the trained decision tree model with rules. <a href="#ac71787c47795b3b0b133cdbd37438242">More...</a><br /></td></tr>
+<tr class="separator:ac71787c47795b3b0b133cdbd37438242"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:acdba07d3897356a75666aa6d5999f490"><td class="memItemLeft" align="right" valign="top">set< text > </td><td class="memItemRight" valign="bottom"><a class="el" href="c45_8sql__in.html#acdba07d3897356a75666aa6d5999f490">c45_genrule</a> (text tree_table_name)</td></tr>
+<tr class="memdesc:acdba07d3897356a75666aa6d5999f490"><td class="mdescLeft"> </td><td class="mdescRight">Display the trained decision tree model with rules. <a href="#acdba07d3897356a75666aa6d5999f490">More...</a><br /></td></tr>
+<tr class="separator:acdba07d3897356a75666aa6d5999f490"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a32d2bcbc016c990991d77b6f6148306d"><td class="memItemLeft" align="right" valign="top">set< text > </td><td class="memItemRight" valign="bottom"><a class="el" href="c45_8sql__in.html#a32d2bcbc016c990991d77b6f6148306d">c45_display</a> (text tree_table, int max_depth)</td></tr>
+<tr class="memdesc:a32d2bcbc016c990991d77b6f6148306d"><td class="mdescLeft"> </td><td class="mdescRight">Display the trained decision tree model with human readable format. <a href="#a32d2bcbc016c990991d77b6f6148306d">More...</a><br /></td></tr>
+<tr class="separator:a32d2bcbc016c990991d77b6f6148306d"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:ad7f190eb8e5d53f4772fac699787c0fe"><td class="memItemLeft" align="right" valign="top">set< text > </td><td class="memItemRight" valign="bottom"><a class="el" href="c45_8sql__in.html#ad7f190eb8e5d53f4772fac699787c0fe">c45_display</a> (text tree_table)</td></tr>
+<tr class="memdesc:ad7f190eb8e5d53f4772fac699787c0fe"><td class="mdescLeft"> </td><td class="mdescRight">Display the whole trained decision tree model with human readable format. <a href="#ad7f190eb8e5d53f4772fac699787c0fe">More...</a><br /></td></tr>
+<tr class="separator:ad7f190eb8e5d53f4772fac699787c0fe"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:afe136e52f498f2ff9e2b91e38e29d670"><td class="memItemLeft" align="right" valign="top">c45_classify_result </td><td class="memItemRight" valign="bottom"><a class="el" href="c45_8sql__in.html#afe136e52f498f2ff9e2b91e38e29d670">c45_classify</a> (text tree_table_name, text classification_table_name, text result_table_name, int verbosity)</td></tr>
+<tr class="memdesc:afe136e52f498f2ff9e2b91e38e29d670"><td class="mdescLeft"> </td><td class="mdescRight">Classify dataset using trained decision tree model. The classification result will be stored in the table which is defined as: <a href="#afe136e52f498f2ff9e2b91e38e29d670">More...</a><br /></td></tr>
+<tr class="separator:afe136e52f498f2ff9e2b91e38e29d670"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:af5eb174eeecd11233409657221586cf1"><td class="memItemLeft" align="right" valign="top">c45_classify_result </td><td class="memItemRight" valign="bottom"><a class="el" href="c45_8sql__in.html#af5eb174eeecd11233409657221586cf1">c45_classify</a> (text tree_table_name, text classification_table_name, text result_table_name)</td></tr>
+<tr class="memdesc:af5eb174eeecd11233409657221586cf1"><td class="mdescLeft"> </td><td class="mdescRight">Classify dataset using trained decision tree model. It runs in quiet mode. The classification result will be stored in the table which is defined as: <a href="#af5eb174eeecd11233409657221586cf1">More...</a><br /></td></tr>
+<tr class="separator:af5eb174eeecd11233409657221586cf1"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a1b634db47e9006d114da0987e80b9601"><td class="memItemLeft" align="right" valign="top">float8 </td><td class="memItemRight" valign="bottom"><a class="el" href="c45_8sql__in.html#a1b634db47e9006d114da0987e80b9601">c45_score</a> (text tree_table_name, text scoring_table_name, int verbosity)</td></tr>
+<tr class="memdesc:a1b634db47e9006d114da0987e80b9601"><td class="mdescLeft"> </td><td class="mdescRight">Check the accuracy of the decision tree model. <a href="#a1b634db47e9006d114da0987e80b9601">More...</a><br /></td></tr>
+<tr class="separator:a1b634db47e9006d114da0987e80b9601"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:af0739749507c1097003dcf529d29fee2"><td class="memItemLeft" align="right" valign="top">float8 </td><td class="memItemRight" valign="bottom"><a class="el" href="c45_8sql__in.html#af0739749507c1097003dcf529d29fee2">c45_score</a> (text tree_table_name, text scoring_table_name)</td></tr>
+<tr class="memdesc:af0739749507c1097003dcf529d29fee2"><td class="mdescLeft"> </td><td class="mdescRight">Check the accuracy of the decision tree model. <a href="#af0739749507c1097003dcf529d29fee2">More...</a><br /></td></tr>
+<tr class="separator:af0739749507c1097003dcf529d29fee2"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:ac25e17ecbc70149aa559018e718fc793"><td class="memItemLeft" align="right" valign="top">boolean </td><td class="memItemRight" valign="bottom"><a class="el" href="c45_8sql__in.html#ac25e17ecbc70149aa559018e718fc793">c45_clean</a> (text result_tree_table_name)</td></tr>
+<tr class="memdesc:ac25e17ecbc70149aa559018e718fc793"><td class="mdescLeft"> </td><td class="mdescRight">Cleanup the trained tree table and any relevant tables. <a href="#ac25e17ecbc70149aa559018e718fc793">More...</a><br /></td></tr>
+<tr class="separator:ac25e17ecbc70149aa559018e718fc793"><td class="memSeparator" colspan="2"> </td></tr>
+</table>
+<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
+<div class="textblock"><dl class="section date"><dt>Date</dt><dd>April 5, 2012</dd></dl>
+<dl class="section see"><dt>See also</dt><dd>For a brief introduction to decision trees, see the module description <a class="el" href="group__grp__dectree.html">Decision Tree (old C4.5 implementation)</a>. </dd></dl>
+</div><h2 class="groupheader">Function Documentation</h2>
+<a class="anchor" id="afe136e52f498f2ff9e2b91e38e29d670"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">c45_classify_result c45_classify </td>
+ <td>(</td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>tree_table_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>classification_table_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>result_table_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">int </td>
+ <td class="paramname"><em>verbosity</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+<p>CREATE TABLE classification_result ( id INT|BIGINT, class SUPPORTED_DATA_TYPE, prob FLOAT );</p>
+<dl class="params"><dt>Parameters</dt><dd>
+ <table class="params">
+ <tr><td class="paramname">tree_table_name</td><td>The name of trained tree. </td></tr>
+ <tr><td class="paramname">classification_table_name</td><td>The name of the table/view with the source data. </td></tr>
+ <tr><td class="paramname">result_table_name</td><td>The name of result table. </td></tr>
+ <tr><td class="paramname">verbosity</td><td>> 0 means this function runs in verbose mode.</td></tr>
+ </table>
+ </dd>
+</dl>
+<dl class="section return"><dt>Returns</dt><dd>A c45_classify_result object. </dd></dl>
+
+</div>
+</div>
+<a class="anchor" id="af5eb174eeecd11233409657221586cf1"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">c45_classify_result c45_classify </td>
+ <td>(</td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>tree_table_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>classification_table_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>result_table_name</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+<p>CREATE TABLE classification_result ( id INT|BIGINT, class SUPPORTED_DATA_TYPE, prob FLOAT );</p>
+<dl class="params"><dt>Parameters</dt><dd>
+ <table class="params">
+ <tr><td class="paramname">tree_table_name</td><td>The name of trained tree. </td></tr>
+ <tr><td class="paramname">classification_table_name</td><td>The name of the table/view with the source data. </td></tr>
+ <tr><td class="paramname">result_table_name</td><td>The name of result table.</td></tr>
+ </table>
+ </dd>
+</dl>
+<dl class="section return"><dt>Returns</dt><dd>A c45_classify_result object. </dd></dl>
+
+</div>
+</div>
+<a class="anchor" id="ac25e17ecbc70149aa559018e718fc793"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">boolean c45_clean </td>
+ <td>(</td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>result_tree_table_name</em></td><td>)</td>
+ <td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+<dl class="params"><dt>Parameters</dt><dd>
+ <table class="params">
+ <tr><td class="paramname">result_tree_table_name</td><td>The name of the table containing the tree's information.</td></tr>
+ </table>
+ </dd>
+</dl>
+<dl class="section return"><dt>Returns</dt><dd>The status of that cleanup operation. </dd></dl>
+
+</div>
+</div>
+<a class="anchor" id="a32d2bcbc016c990991d77b6f6148306d"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">set<text> c45_display </td>
+ <td>(</td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>tree_table</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">int </td>
+ <td class="paramname"><em>max_depth</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+<dl class="params"><dt>Parameters</dt><dd>
+ <table class="params">
+ <tr><td class="paramname">tree_table</td><td>The name of the table containing the tree's information. </td></tr>
+ <tr><td class="paramname">max_depth</td><td>The max depth to be displayed. If null, this function will show all levels.</td></tr>
+ </table>
+ </dd>
+</dl>
+<dl class="section return"><dt>Returns</dt><dd>The text representing the tree with human readable format. </dd></dl>
+
+</div>
+</div>
+<a class="anchor" id="ad7f190eb8e5d53f4772fac699787c0fe"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">set<text> c45_display </td>
+ <td>(</td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>tree_table</em></td><td>)</td>
+ <td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+<dl class="params"><dt>Parameters</dt><dd>
+ <table class="params">
+ <tr><td class="paramname">tree_table</td><td>The name of the table containing the tree's information.</td></tr>
+ </table>
+ </dd>
+</dl>
+<dl class="section return"><dt>Returns</dt><dd>The text representing the tree with human readable format. </dd></dl>
+
+</div>
+</div>
+<a class="anchor" id="ac71787c47795b3b0b133cdbd37438242"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">set<text> c45_genrule </td>
+ <td>(</td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>tree_table_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">int </td>
+ <td class="paramname"><em>verbosity</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+<dl class="params"><dt>Parameters</dt><dd>
+ <table class="params">
+ <tr><td class="paramname">tree_table_name</td><td>The name of the table containing the tree's information. </td></tr>
+ <tr><td class="paramname">verbosity</td><td>If >= 1 will run in verbose mode.</td></tr>
+ </table>
+ </dd>
+</dl>
+<dl class="section return"><dt>Returns</dt><dd>The rule representation text for a decision tree. </dd></dl>
+
+</div>
+</div>
+<a class="anchor" id="acdba07d3897356a75666aa6d5999f490"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">set<text> c45_genrule </td>
+ <td>(</td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>tree_table_name</em></td><td>)</td>
+ <td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+<dl class="params"><dt>Parameters</dt><dd>
+ <table class="params">
+ <tr><td class="paramname">tree_table_name</td><td>The name of the table containing the tree's information.</td></tr>
+ </table>
+ </dd>
+</dl>
+<dl class="section return"><dt>Returns</dt><dd>The rule representation text for a decision tree. </dd></dl>
+
+</div>
+</div>
+<a class="anchor" id="a1b634db47e9006d114da0987e80b9601"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">float8 c45_score </td>
+ <td>(</td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>tree_table_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>scoring_table_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">int </td>
+ <td class="paramname"><em>verbosity</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+<dl class="params"><dt>Parameters</dt><dd>
+ <table class="params">
+ <tr><td class="paramname">tree_table_name</td><td>The name of the trained tree. </td></tr>
+ <tr><td class="paramname">scoring_table_name</td><td>The name of the table/view with the source data. </td></tr>
+ <tr><td class="paramname">verbosity</td><td>> 0 means this function runs in verbose mode.</td></tr>
+ </table>
+ </dd>
+</dl>
+<dl class="section return"><dt>Returns</dt><dd>The estimated accuracy information. </dd></dl>
+
+</div>
+</div>
+<a class="anchor" id="af0739749507c1097003dcf529d29fee2"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">float8 c45_score </td>
+ <td>(</td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>tree_table_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>scoring_table_name</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+<dl class="params"><dt>Parameters</dt><dd>
+ <table class="params">
+ <tr><td class="paramname">tree_table_name</td><td>The name of the trained tree. </td></tr>
+ <tr><td class="paramname">scoring_table_name</td><td>The name of the table/view with the source data.</td></tr>
+ </table>
+ </dd>
+</dl>
+<dl class="section return"><dt>Returns</dt><dd>The estimated accuracy information. </dd></dl>
+
+</div>
+</div>
+<a class="anchor" id="a4fbee855d22101d15d195d573189eb98"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">c45_train_result c45_train </td>
+ <td>(</td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>split_criterion</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>training_table_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>result_tree_table_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>validation_table_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>continuous_feature_names</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>feature_col_names</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>id_col_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>class_col_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">float </td>
+ <td class="paramname"><em>confidence_level</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>how2handle_missing_value</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">int </td>
+ <td class="paramname"><em>max_tree_depth</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">float </td>
+ <td class="paramname"><em>node_prune_threshold</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">float </td>
+ <td class="paramname"><em>node_split_threshold</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">int </td>
+ <td class="paramname"><em>verbosity</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+<dl class="params"><dt>Parameters</dt><dd>
+ <table class="params">
+ <tr><td class="paramname">split_criterion</td><td>The name of the split criterion that should be used for tree construction. The valid values are ‘infogain’, ‘gainratio’, and ‘gini’. It can't be NULL. Information gain(infogain) and gini index(gini) are biased toward multivalued attributes. Gain ratio(gainratio) adjusts for this bias. However, it tends to prefer unbalanced splits in which one partition is much smaller than the others. </td></tr>
+ <tr><td class="paramname">training_table_name</td><td>The name of the table/view with the source data. </td></tr>
+ <tr><td class="paramname">result_tree_table_name</td><td>The name of the table where the resulting DT will be kept. </td></tr>
+ <tr><td class="paramname">validation_table_name</td><td>The name of the table/view that contains the validation set used for tree pruning. The default is NULL, in which case we will not do tree pruning. </td></tr>
+ <tr><td class="paramname">continuous_feature_names</td><td>A comma-separated list of the names of features whose values are continuous. The default is null, which means there are no continuous features in the training table. </td></tr>
+ <tr><td class="paramname">feature_col_names</td><td>A comma-separated list of the names of table columns, each of which defines a feature. The default value is null, which means all the columns in the training table, except columns named ‘id’ and ‘class’, will be used as features. </td></tr>
+ <tr><td class="paramname">id_col_name</td><td>The name of the column containing an ID for each record. </td></tr>
+ <tr><td class="paramname">class_col_name</td><td>The name of the column containing the labeled class. </td></tr>
+ <tr><td class="paramname">confidence_level</td><td>A statistical confidence interval of the resubstitution error. </td></tr>
+ <tr><td class="paramname">how2handle_missing_value</td><td>The way to handle missing value. The valid value is 'explicit' or 'ignore'. </td></tr>
+ <tr><td class="paramname">max_tree_depth</td><td>Specifies the maximum number of levels in the result DT to avoid overgrown DTs. </td></tr>
+ <tr><td class="paramname">node_prune_threshold</td><td>The minimum percentage of the number of records required in a child node. It can't be NULL. The range of it is in [0.0, 1.0]. This threshold only applies to the non-root nodes. Therefore, if its value is 1, then the trained tree only has one node (the root node); if its value is 0, then no nodes will be pruned by this parameter. </td></tr>
+ <tr><td class="paramname">node_split_threshold</td><td>The minimum percentage of the number of records required in a node in order for a further split to be possible. It can't be NULL. The range of it is in [0.0, 1.0]. If it's value is 1, then the trained tree only has two levels, since only the root node can grow; if its value is 0, then trees can grow extensively. </td></tr>
+ <tr><td class="paramname">verbosity</td><td>> 0 means this function runs in verbose mode.</td></tr>
+ </table>
+ </dd>
+</dl>
+<dl class="section return"><dt>Returns</dt><dd>An c45_train_result object. </dd></dl>
+
+</div>
+</div>
+<a class="anchor" id="a6c039416b94686b915e2a4c1133a5d44"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">c45_train_result c45_train </td>
+ <td>(</td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>split_criterion</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>training_table_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>result_tree_table_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>validation_table_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>continuous_feature_names</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>feature_col_names</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>id_col_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>class_col_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">float </td>
+ <td class="paramname"><em>confidence_level</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>how2handle_missing_value</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+<dl class="params"><dt>Parameters</dt><dd>
+ <table class="params">
+ <tr><td class="paramname">split_criterion</td><td>The name of the split criterion that should be used for tree construction. Possible values are ‘gain’, ‘gainratio’, and ‘gini’. </td></tr>
+ <tr><td class="paramname">training_table_name</td><td>The name of the table/view with the source data. </td></tr>
+ <tr><td class="paramname">result_tree_table_name</td><td>The name of the table where the resulting DT will be kept. </td></tr>
+ <tr><td class="paramname">validation_table_name</td><td>The name of the table/view that contains the validation set used for tree pruning. The default is NULL, in which case we will not do tree pruning. </td></tr>
+ <tr><td class="paramname">continuous_feature_names</td><td>A comma-separated list of the names of features whose values are continuous. The default is null, which means there are no continuous features in the training table. </td></tr>
+ <tr><td class="paramname">feature_col_names</td><td>A comma-separated list of the names of table columns, each of which defines a feature. The default value is null, which means all the columns in the training table, except columns named ‘id’ and ‘class’, will be used as features. </td></tr>
+ <tr><td class="paramname">id_col_name</td><td>The name of the column containing an ID for each record. </td></tr>
+ <tr><td class="paramname">class_col_name</td><td>The name of the column containing the labeled class. </td></tr>
+ <tr><td class="paramname">confidence_level</td><td>A statistical confidence interval of the resubstitution error. </td></tr>
+ <tr><td class="paramname">how2handle_missing_value</td><td>The way to handle missing value. The valid value is 'explicit' or 'ignore'.</td></tr>
+ </table>
+ </dd>
+</dl>
+<dl class="section return"><dt>Returns</dt><dd>An c45_train_result object.</dd></dl>
+<dl class="section note"><dt>Note</dt><dd>This calls the long form of C45 with the following default parameters:<ul>
+<li>max_tree_deapth := 10</li>
+<li>node_prune_threshold := 0.001</li>
+<li>node_split_threshold := 0.01</li>
+<li>verbosity := 0 </li>
+</ul>
+</dd></dl>
+
+</div>
+</div>
+<a class="anchor" id="a18b30ff1a063e7cd16274bf7ab2a71dc"></a>
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">c45_train_result c45_train </td>
+ <td>(</td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>split_criterion</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>training_table_name</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">text </td>
+ <td class="paramname"><em>result_tree_table_name</em> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+<dl class="params"><dt>Parameters</dt><dd>
+ <table class="params">
+ <tr><td class="paramname">split_criterion</td><td>The name of the split criterion that should be used for tree construction. Possible values are ‘gain’, ‘gainratio’, and ‘gini’. </td></tr>
+ <tr><td class="paramname">training_table_name</td><td>The name of the table/view with the source data. </td></tr>
+ <tr><td class="paramname">result_tree_table_name</td><td>The name of the table where the resulting DT will be kept.</td></tr>
+ </table>
+ </dd>
+</dl>
+<dl class="section return"><dt>Returns</dt><dd>An c45_train_result object.</dd></dl>
+<dl class="section note"><dt>Note</dt><dd>This calls the above short form of C45 with the following default parameters:<ul>
+<li>validation_table_name := NULL</li>
+<li>continuous_feature_names := NULL</li>
+<li>id_column_name := 'id'</li>
+<li>class_column_name := 'class'</li>
+<li>confidence_level := 25</li>
+<li>how2handle_missing_value := 'explicit'</li>
+<li>max_tree_deapth := 10</li>
+<li>node_prune_threshold := 0.001</li>
+<li>node_split_threshold := 0.01</li>
+<li>verbosity := 0 </li>
+</ul>
+</dd></dl>
+
+</div>
+</div>
+</div><!-- contents -->
+</div><!-- doc-content -->
+<!-- start footer part -->
+<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
+ <ul>
+ <li class="navelem"><a class="el" href="dir_704eb8350b43e1ca74c0f90ed1ba450e.html">methods</a></li><li class="navelem"><a class="el" href="dir_fbc4f2259ae1d6f6cc75298ebbd15532.html">cart</a></li><li class="navelem"><a class="el" href="dir_42a199e31e82b0c41cf7961a25e597db.html">src</a></li><li class="navelem"><a class="el" href="dir_64bd18b6b0e4b6a9c2cd2ca1d5a05b4c.html">pg_gp</a></li><li class="navelem"><a class="el" href="c45_8sql__in.html">c45.sql_in</a></li>
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