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<div id="projectbrief">Set of algorithms implemented in C.</div>
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<div class="headertitle"><div class="title">K-Means Clustering Algorithm<div class="ingroups"><a class="el" href="../../d9/d66/group__machine__learning.html">Machine learning algorithms</a></div></div></div>
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Collaboration diagram for K-Means Clustering Algorithm:</div>
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Data Structures</h2></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct  </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d1/d5e/structobservation.html">observation</a></td></tr>
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<tr class="separator:"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct  </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d1/d99/structcluster.html">cluster</a></td></tr>
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Typedefs</h2></td></tr>
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typedef struct <a class="el" href="../../d1/d5e/structobservation.html">observation</a> </td><td class="memItemRight" valign="bottom"><b>observation</b></td></tr>
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typedef struct <a class="el" href="../../d1/d99/structcluster.html">cluster</a> </td><td class="memItemRight" valign="bottom"><b>cluster</b></td></tr>
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</table><table class="memberdecls">
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a id="func-members" name="func-members"></a>
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Functions</h2></td></tr>
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<tr class="memitem:gad339c41d3ee9e6729aca9e9ab3f7d2d9" id="r_gad339c41d3ee9e6729aca9e9ab3f7d2d9"><td class="memItemLeft" align="right" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d71/group__k__means.html#gad339c41d3ee9e6729aca9e9ab3f7d2d9">calculateNearst</a> (<a class="el" href="../../d1/d5e/structobservation.html">observation</a> *o, <a class="el" href="../../d1/d99/structcluster.html">cluster</a> clusters[], int k)</td></tr>
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<tr class="memitem:gadee39a3f17bf5144df5592e48dbfc9f7" id="r_gadee39a3f17bf5144df5592e48dbfc9f7"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d71/group__k__means.html#gadee39a3f17bf5144df5592e48dbfc9f7">calculateCentroid</a> (<a class="el" href="../../d1/d5e/structobservation.html">observation</a> observations[], size_t size, <a class="el" href="../../d1/d99/structcluster.html">cluster</a> *centroid)</td></tr>
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<tr class="separator:gadee39a3f17bf5144df5592e48dbfc9f7"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:gaf6259432561e794dea0e060f482d15e2" id="r_gaf6259432561e794dea0e060f482d15e2"><td class="memItemLeft" align="right" valign="top"><a class="el" href="../../d1/d99/structcluster.html">cluster</a> * </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d71/group__k__means.html#gaf6259432561e794dea0e060f482d15e2">kMeans</a> (<a class="el" href="../../d1/d5e/structobservation.html">observation</a> observations[], size_t size, int k)</td></tr>
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<tr class="separator:gaf6259432561e794dea0e060f482d15e2"><td class="memSeparator" colspan="2"> </td></tr>
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</table>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
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<h2 class="groupheader">Function Documentation</h2>
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<a id="gadee39a3f17bf5144df5592e48dbfc9f7" name="gadee39a3f17bf5144df5592e48dbfc9f7"></a>
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<h2 class="memtitle"><span class="permalink"><a href="#gadee39a3f17bf5144df5592e48dbfc9f7">◆ </a></span>calculateCentroid()</h2>
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<td class="memname">void calculateCentroid </td>
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<td>(</td>
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<td class="paramtype"><a class="el" href="../../d1/d5e/structobservation.html">observation</a> </td>
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<td class="paramname"><em>observations</em>[], </td>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">size_t </td>
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<td class="paramname"><em>size</em>, </td>
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<td class="paramkey"></td>
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<td class="paramtype"><a class="el" href="../../d1/d99/structcluster.html">cluster</a> * </td>
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<td class="paramname"><em>centroid</em> </td>
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<td></td>
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<td>)</td>
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<td></td><td></td>
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<p>Calculate centoid and assign it to the cluster variable</p>
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<dl class="params"><dt>Parameters</dt><dd>
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<table class="params">
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<tr><td class="paramname">observations</td><td>an array of observations whose centroid is calculated </td></tr>
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<tr><td class="paramname">size</td><td>size of the observations array </td></tr>
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<tr><td class="paramname">centroid</td><td>a reference to cluster object to store information of centroid </td></tr>
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</table>
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</dd>
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<div class="fragment"><div class="line"><span class="lineno"> 99</span>{</div>
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<div class="line"><span class="lineno"> 100</span> <span class="keywordtype">size_t</span> i = 0;</div>
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<div class="line"><span class="lineno"> 101</span> centroid-><a class="code hl_variable" href="../../d1/d99/structcluster.html#a13278ef636c1d9bd9ce8fad736f4c570">x</a> = 0;</div>
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<div class="line"><span class="lineno"> 102</span> centroid-><a class="code hl_variable" href="../../d1/d99/structcluster.html#a10fa7010c12d0f03a422d68321495479">y</a> = 0;</div>
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<div class="line"><span class="lineno"> 103</span> centroid-><a class="code hl_variable" href="../../d1/d99/structcluster.html#aaacf0562ee2d9e8866c66ddaa6527c2b">count</a> = size;</div>
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<div class="line"><span class="lineno"> 104</span> <span class="keywordflow">for</span> (; i < size; i++)</div>
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<div class="line"><span class="lineno"> 105</span> {</div>
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<div class="line"><span class="lineno"> 106</span> centroid-><a class="code hl_variable" href="../../d1/d99/structcluster.html#a13278ef636c1d9bd9ce8fad736f4c570">x</a> += observations[i].<a class="code hl_variable" href="../../d1/d5e/structobservation.html#a04f3dcfd59dd91353395e35c9831fade">x</a>;</div>
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<div class="line"><span class="lineno"> 107</span> centroid-><a class="code hl_variable" href="../../d1/d99/structcluster.html#a10fa7010c12d0f03a422d68321495479">y</a> += observations[i].<a class="code hl_variable" href="../../d1/d5e/structobservation.html#ab6be1fa7024b2d5f3a30d6c6b70efdd7">y</a>;</div>
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<div class="line"><span class="lineno"> 108</span> observations[i].<a class="code hl_variable" href="../../d1/d5e/structobservation.html#a2db8ace685c08aa7b52f5a28b0843aab">group</a> = 0;</div>
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<div class="line"><span class="lineno"> 109</span> }</div>
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<div class="line"><span class="lineno"> 110</span> centroid-><a class="code hl_variable" href="../../d1/d99/structcluster.html#a13278ef636c1d9bd9ce8fad736f4c570">x</a> /= centroid-><a class="code hl_variable" href="../../d1/d99/structcluster.html#aaacf0562ee2d9e8866c66ddaa6527c2b">count</a>;</div>
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<div class="line"><span class="lineno"> 111</span> centroid-><a class="code hl_variable" href="../../d1/d99/structcluster.html#a10fa7010c12d0f03a422d68321495479">y</a> /= centroid-><a class="code hl_variable" href="../../d1/d99/structcluster.html#aaacf0562ee2d9e8866c66ddaa6527c2b">count</a>;</div>
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<div class="line"><span class="lineno"> 112</span>}</div>
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<div class="ttc" id="astructcluster_html_a10fa7010c12d0f03a422d68321495479"><div class="ttname"><a href="../../d1/d99/structcluster.html#a10fa7010c12d0f03a422d68321495479">cluster::y</a></div><div class="ttdeci">double y</div><div class="ttdoc">ordinate of centroid of this cluster</div><div class="ttdef"><b>Definition</b> k_means_clustering.c:55</div></div>
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<div class="ttc" id="astructcluster_html_a13278ef636c1d9bd9ce8fad736f4c570"><div class="ttname"><a href="../../d1/d99/structcluster.html#a13278ef636c1d9bd9ce8fad736f4c570">cluster::x</a></div><div class="ttdeci">double x</div><div class="ttdoc">abscissa centroid of this cluster</div><div class="ttdef"><b>Definition</b> k_means_clustering.c:54</div></div>
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<div class="ttc" id="astructcluster_html_aaacf0562ee2d9e8866c66ddaa6527c2b"><div class="ttname"><a href="../../d1/d99/structcluster.html#aaacf0562ee2d9e8866c66ddaa6527c2b">cluster::count</a></div><div class="ttdeci">size_t count</div><div class="ttdoc">count of observations present in this cluster</div><div class="ttdef"><b>Definition</b> k_means_clustering.c:56</div></div>
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<div class="ttc" id="astructobservation_html_a04f3dcfd59dd91353395e35c9831fade"><div class="ttname"><a href="../../d1/d5e/structobservation.html#a04f3dcfd59dd91353395e35c9831fade">observation::x</a></div><div class="ttdeci">double x</div><div class="ttdoc">abscissa of 2D data point</div><div class="ttdef"><b>Definition</b> k_means_clustering.c:40</div></div>
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<div class="ttc" id="astructobservation_html_a2db8ace685c08aa7b52f5a28b0843aab"><div class="ttname"><a href="../../d1/d5e/structobservation.html#a2db8ace685c08aa7b52f5a28b0843aab">observation::group</a></div><div class="ttdeci">int group</div><div class="ttdoc">the group no in which this observation would go</div><div class="ttdef"><b>Definition</b> k_means_clustering.c:42</div></div>
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<div class="ttc" id="astructobservation_html_ab6be1fa7024b2d5f3a30d6c6b70efdd7"><div class="ttname"><a href="../../d1/d5e/structobservation.html#ab6be1fa7024b2d5f3a30d6c6b70efdd7">observation::y</a></div><div class="ttdeci">double y</div><div class="ttdoc">ordinate of 2D data point</div><div class="ttdef"><b>Definition</b> k_means_clustering.c:41</div></div>
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<a id="gad339c41d3ee9e6729aca9e9ab3f7d2d9" name="gad339c41d3ee9e6729aca9e9ab3f7d2d9"></a>
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<h2 class="memtitle"><span class="permalink"><a href="#gad339c41d3ee9e6729aca9e9ab3f7d2d9">◆ </a></span>calculateNearst()</h2>
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<td class="memname">int calculateNearst </td>
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<td>(</td>
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<td class="paramtype"><a class="el" href="../../d1/d5e/structobservation.html">observation</a> * </td>
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<td class="paramname"><em>o</em>, </td>
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<td class="paramkey"></td>
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<td class="paramtype"><a class="el" href="../../d1/d99/structcluster.html">cluster</a> </td>
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<td class="paramname"><em>clusters</em>[], </td>
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<td class="paramtype">int </td>
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<td class="paramname"><em>k</em> </td>
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<td></td>
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<td>)</td>
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<p>Returns the index of centroid nearest to given observation</p>
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<dl class="params"><dt>Parameters</dt><dd>
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<table class="params">
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<tr><td class="paramname">o</td><td>observation </td></tr>
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<tr><td class="paramname">clusters</td><td>array of cluster having centroids coordinates </td></tr>
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<tr><td class="paramname">k</td><td>size of clusters array</td></tr>
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</table>
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<dl class="section return"><dt>Returns</dt><dd>the index of nearest centroid for given observation </dd></dl>
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<div class="fragment"><div class="line"><span class="lineno"> 70</span>{</div>
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<div class="line"><span class="lineno"> 71</span> <span class="keywordtype">double</span> minD = DBL_MAX;</div>
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<div class="line"><span class="lineno"> 72</span> <span class="keywordtype">double</span> dist = 0;</div>
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<div class="line"><span class="lineno"> 73</span> <span class="keywordtype">int</span> index = -1;</div>
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<div class="line"><span class="lineno"> 74</span> <span class="keywordtype">int</span> i = 0;</div>
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<div class="line"><span class="lineno"> 75</span> <span class="keywordflow">for</span> (; i < k; i++)</div>
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<div class="line"><span class="lineno"> 76</span> {</div>
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<div class="line"><span class="lineno"> 77</span> <span class="comment">/* Calculate Squared Distance*/</span></div>
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<div class="line"><span class="lineno"> 78</span> dist = (clusters[i].<a class="code hl_variable" href="../../d1/d99/structcluster.html#a13278ef636c1d9bd9ce8fad736f4c570">x</a> - o-><a class="code hl_variable" href="../../d1/d5e/structobservation.html#a04f3dcfd59dd91353395e35c9831fade">x</a>) * (clusters[i].x - o-><a class="code hl_variable" href="../../d1/d5e/structobservation.html#a04f3dcfd59dd91353395e35c9831fade">x</a>) +</div>
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<div class="line"><span class="lineno"> 79</span> (clusters[i].<a class="code hl_variable" href="../../d1/d99/structcluster.html#a10fa7010c12d0f03a422d68321495479">y</a> - o-><a class="code hl_variable" href="../../d1/d5e/structobservation.html#ab6be1fa7024b2d5f3a30d6c6b70efdd7">y</a>) * (clusters[i].y - o-><a class="code hl_variable" href="../../d1/d5e/structobservation.html#ab6be1fa7024b2d5f3a30d6c6b70efdd7">y</a>);</div>
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<div class="line"><span class="lineno"> 80</span> <span class="keywordflow">if</span> (dist < minD)</div>
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<div class="line"><span class="lineno"> 81</span> {</div>
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<div class="line"><span class="lineno"> 82</span> minD = dist;</div>
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<div class="line"><span class="lineno"> 83</span> index = i;</div>
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<div class="line"><span class="lineno"> 84</span> }</div>
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<div class="line"><span class="lineno"> 85</span> }</div>
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<div class="line"><span class="lineno"> 86</span> <span class="keywordflow">return</span> index;</div>
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<div class="line"><span class="lineno"> 87</span>}</div>
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<a id="gaf6259432561e794dea0e060f482d15e2" name="gaf6259432561e794dea0e060f482d15e2"></a>
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<h2 class="memtitle"><span class="permalink"><a href="#gaf6259432561e794dea0e060f482d15e2">◆ </a></span>kMeans()</h2>
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<div class="memitem">
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<td class="memname"><a class="el" href="../../d1/d99/structcluster.html">cluster</a> * kMeans </td>
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<td>(</td>
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<td class="paramtype"><a class="el" href="../../d1/d5e/structobservation.html">observation</a> </td>
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<td class="paramname"><em>observations</em>[], </td>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">size_t </td>
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<td class="paramname"><em>size</em>, </td>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">int </td>
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<td class="paramname"><em>k</em> </td>
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<td></td>
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<td>)</td>
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</div><div class="memdoc">
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<p>–K Means Algorithm–</p><ol type="1">
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<li>Assign each observation to one of k groups creating a random initial clustering</li>
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<li>Find the centroid of observations for each cluster to form new centroids</li>
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<li>Find the centroid which is nearest for each observation among the calculated centroids</li>
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<li>Assign the observation to its nearest centroid to create a new clustering.</li>
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<li>Repeat step 2,3,4 until there is no change the current clustering and is same as last clustering.</li>
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</ol>
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<dl class="params"><dt>Parameters</dt><dd>
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<table class="params">
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<tr><td class="paramname">observations</td><td>an array of observations to cluster </td></tr>
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<tr><td class="paramname">size</td><td>size of observations array </td></tr>
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<tr><td class="paramname">k</td><td>no of clusters to be made</td></tr>
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</table>
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</dd>
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</dl>
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<dl class="section return"><dt>Returns</dt><dd>pointer to cluster object </dd></dl>
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<div class="fragment"><div class="line"><span class="lineno"> 135</span>{</div>
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<div class="line"><span class="lineno"> 136</span> <a class="code hl_struct" href="../../d1/d99/structcluster.html">cluster</a>* clusters = NULL;</div>
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<div class="line"><span class="lineno"> 137</span> <span class="keywordflow">if</span> (k <= 1)</div>
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<div class="line"><span class="lineno"> 138</span> {</div>
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<div class="line"><span class="lineno"> 139</span> <span class="comment">/*</span></div>
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<div class="line"><span class="lineno"> 140</span><span class="comment"> If we have to cluster them only in one group</span></div>
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<div class="line"><span class="lineno"> 141</span><span class="comment"> then calculate centroid of observations and</span></div>
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<div class="line"><span class="lineno"> 142</span><span class="comment"> that will be a ingle cluster</span></div>
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<div class="line"><span class="lineno"> 143</span><span class="comment"> */</span></div>
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<div class="line"><span class="lineno"> 144</span> clusters = (<a class="code hl_struct" href="../../d1/d99/structcluster.html">cluster</a>*)<a class="code hl_define" href="../../d2/ddd/malloc__dbg_8h.html#a725f50ecaf1959d96de79b36b4788fee">malloc</a>(<span class="keyword">sizeof</span>(<a class="code hl_struct" href="../../d1/d99/structcluster.html">cluster</a>));</div>
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<div class="line"><span class="lineno"> 145</span> memset(clusters, 0, <span class="keyword">sizeof</span>(<a class="code hl_struct" href="../../d1/d99/structcluster.html">cluster</a>));</div>
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<div class="line"><span class="lineno"> 146</span> <a class="code hl_function" href="../../d8/d71/group__k__means.html#gadee39a3f17bf5144df5592e48dbfc9f7">calculateCentroid</a>(observations, size, clusters);</div>
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<div class="line"><span class="lineno"> 147</span> }</div>
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<div class="line"><span class="lineno"> 148</span> <span class="keywordflow">else</span> <span class="keywordflow">if</span> (k < size)</div>
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<div class="line"><span class="lineno"> 149</span> {</div>
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<div class="line"><span class="lineno"> 150</span> clusters = <a class="code hl_define" href="../../d2/ddd/malloc__dbg_8h.html#a725f50ecaf1959d96de79b36b4788fee">malloc</a>(<span class="keyword">sizeof</span>(<a class="code hl_struct" href="../../d1/d99/structcluster.html">cluster</a>) * k);</div>
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<div class="line"><span class="lineno"> 151</span> memset(clusters, 0, k * <span class="keyword">sizeof</span>(<a class="code hl_struct" href="../../d1/d99/structcluster.html">cluster</a>));</div>
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<div class="line"><span class="lineno"> 152</span> <span class="comment">/* STEP 1 */</span></div>
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<div class="line"><span class="lineno"> 153</span> <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j < size; j++)</div>
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<div class="line"><span class="lineno"> 154</span> {</div>
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<div class="line"><span class="lineno"> 155</span> observations[j].<a class="code hl_variable" href="../../d1/d5e/structobservation.html#a2db8ace685c08aa7b52f5a28b0843aab">group</a> = rand() % k;</div>
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<div class="line"><span class="lineno"> 156</span> }</div>
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<div class="line"><span class="lineno"> 157</span> <span class="keywordtype">size_t</span> changed = 0;</div>
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<div class="line"><span class="lineno"> 158</span> <span class="keywordtype">size_t</span> minAcceptedError =</div>
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<div class="line"><span class="lineno"> 159</span> size /</div>
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<div class="line"><span class="lineno"> 160</span> 10000; <span class="comment">// Do until 99.99 percent points are in correct cluster</span></div>
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<div class="line"><span class="lineno"> 161</span> <span class="keywordtype">int</span> t = 0;</div>
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<div class="line"><span class="lineno"> 162</span> <span class="keywordflow">do</span></div>
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<div class="line"><span class="lineno"> 163</span> {</div>
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<div class="line"><span class="lineno"> 164</span> <span class="comment">/* Initialize clusters */</span></div>
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<div class="line"><span class="lineno"> 165</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < k; i++)</div>
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<div class="line"><span class="lineno"> 166</span> {</div>
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<div class="line"><span class="lineno"> 167</span> clusters[i].<a class="code hl_variable" href="../../d1/d99/structcluster.html#a13278ef636c1d9bd9ce8fad736f4c570">x</a> = 0;</div>
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<div class="line"><span class="lineno"> 168</span> clusters[i].<a class="code hl_variable" href="../../d1/d99/structcluster.html#a10fa7010c12d0f03a422d68321495479">y</a> = 0;</div>
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<div class="line"><span class="lineno"> 169</span> clusters[i].<a class="code hl_variable" href="../../d1/d99/structcluster.html#aaacf0562ee2d9e8866c66ddaa6527c2b">count</a> = 0;</div>
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<div class="line"><span class="lineno"> 170</span> }</div>
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<div class="line"><span class="lineno"> 171</span> <span class="comment">/* STEP 2*/</span></div>
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<div class="line"><span class="lineno"> 172</span> <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j < size; j++)</div>
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<div class="line"><span class="lineno"> 173</span> {</div>
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<div class="line"><span class="lineno"> 174</span> t = observations[j].<a class="code hl_variable" href="../../d1/d5e/structobservation.html#a2db8ace685c08aa7b52f5a28b0843aab">group</a>;</div>
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<div class="line"><span class="lineno"> 175</span> clusters[t].<a class="code hl_variable" href="../../d1/d99/structcluster.html#a13278ef636c1d9bd9ce8fad736f4c570">x</a> += observations[j].<a class="code hl_variable" href="../../d1/d5e/structobservation.html#a04f3dcfd59dd91353395e35c9831fade">x</a>;</div>
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<div class="line"><span class="lineno"> 176</span> clusters[t].<a class="code hl_variable" href="../../d1/d99/structcluster.html#a10fa7010c12d0f03a422d68321495479">y</a> += observations[j].<a class="code hl_variable" href="../../d1/d5e/structobservation.html#ab6be1fa7024b2d5f3a30d6c6b70efdd7">y</a>;</div>
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<div class="line"><span class="lineno"> 177</span> clusters[t].<a class="code hl_variable" href="../../d1/d99/structcluster.html#aaacf0562ee2d9e8866c66ddaa6527c2b">count</a>++;</div>
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<div class="line"><span class="lineno"> 178</span> }</div>
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<div class="line"><span class="lineno"> 179</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < k; i++)</div>
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<div class="line"><span class="lineno"> 180</span> {</div>
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<div class="line"><span class="lineno"> 181</span> clusters[i].<a class="code hl_variable" href="../../d1/d99/structcluster.html#a13278ef636c1d9bd9ce8fad736f4c570">x</a> /= clusters[i].<a class="code hl_variable" href="../../d1/d99/structcluster.html#aaacf0562ee2d9e8866c66ddaa6527c2b">count</a>;</div>
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<div class="line"><span class="lineno"> 182</span> clusters[i].<a class="code hl_variable" href="../../d1/d99/structcluster.html#a10fa7010c12d0f03a422d68321495479">y</a> /= clusters[i].<a class="code hl_variable" href="../../d1/d99/structcluster.html#aaacf0562ee2d9e8866c66ddaa6527c2b">count</a>;</div>
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<div class="line"><span class="lineno"> 183</span> }</div>
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<div class="line"><span class="lineno"> 184</span> <span class="comment">/* STEP 3 and 4 */</span></div>
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<div class="line"><span class="lineno"> 185</span> changed = 0; <span class="comment">// this variable stores change in clustering</span></div>
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<div class="line"><span class="lineno"> 186</span> <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j < size; j++)</div>
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<div class="line"><span class="lineno"> 187</span> {</div>
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<div class="line"><span class="lineno"> 188</span> t = <a class="code hl_function" href="../../d8/d71/group__k__means.html#gad339c41d3ee9e6729aca9e9ab3f7d2d9">calculateNearst</a>(observations + j, clusters, k);</div>
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<div class="line"><span class="lineno"> 189</span> <span class="keywordflow">if</span> (t != observations[j].group)</div>
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<div class="line"><span class="lineno"> 190</span> {</div>
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<div class="line"><span class="lineno"> 191</span> changed++;</div>
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<div class="line"><span class="lineno"> 192</span> observations[j].<a class="code hl_variable" href="../../d1/d5e/structobservation.html#a2db8ace685c08aa7b52f5a28b0843aab">group</a> = t;</div>
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<div class="line"><span class="lineno"> 193</span> }</div>
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<div class="line"><span class="lineno"> 194</span> }</div>
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<div class="line"><span class="lineno"> 195</span> } <span class="keywordflow">while</span> (changed > minAcceptedError); <span class="comment">// Keep on grouping until we have</span></div>
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<div class="line"><span class="lineno"> 196</span> <span class="comment">// got almost best clustering</span></div>
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<div class="line"><span class="lineno"> 197</span> }</div>
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<div class="line"><span class="lineno"> 198</span> <span class="keywordflow">else</span></div>
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<div class="line"><span class="lineno"> 199</span> {</div>
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<div class="line"><span class="lineno"> 200</span> <span class="comment">/* If no of clusters is more than observations</span></div>
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<div class="line"><span class="lineno"> 201</span><span class="comment"> each observation can be its own cluster</span></div>
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<div class="line"><span class="lineno"> 202</span><span class="comment"> */</span></div>
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<div class="line"><span class="lineno"> 203</span> clusters = (<a class="code hl_struct" href="../../d1/d99/structcluster.html">cluster</a>*)<a class="code hl_define" href="../../d2/ddd/malloc__dbg_8h.html#a725f50ecaf1959d96de79b36b4788fee">malloc</a>(<span class="keyword">sizeof</span>(<a class="code hl_struct" href="../../d1/d99/structcluster.html">cluster</a>) * k);</div>
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<div class="line"><span class="lineno"> 204</span> memset(clusters, 0, k * <span class="keyword">sizeof</span>(<a class="code hl_struct" href="../../d1/d99/structcluster.html">cluster</a>));</div>
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<div class="line"><span class="lineno"> 205</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j < size; j++)</div>
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<div class="line"><span class="lineno"> 206</span> {</div>
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<div class="line"><span class="lineno"> 207</span> clusters[j].<a class="code hl_variable" href="../../d1/d99/structcluster.html#a13278ef636c1d9bd9ce8fad736f4c570">x</a> = observations[j].<a class="code hl_variable" href="../../d1/d5e/structobservation.html#a04f3dcfd59dd91353395e35c9831fade">x</a>;</div>
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<div class="line"><span class="lineno"> 208</span> clusters[j].<a class="code hl_variable" href="../../d1/d99/structcluster.html#a10fa7010c12d0f03a422d68321495479">y</a> = observations[j].<a class="code hl_variable" href="../../d1/d5e/structobservation.html#ab6be1fa7024b2d5f3a30d6c6b70efdd7">y</a>;</div>
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<div class="line"><span class="lineno"> 209</span> clusters[j].<a class="code hl_variable" href="../../d1/d99/structcluster.html#aaacf0562ee2d9e8866c66ddaa6527c2b">count</a> = 1;</div>
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<div class="line"><span class="lineno"> 210</span> observations[j].<a class="code hl_variable" href="../../d1/d5e/structobservation.html#a2db8ace685c08aa7b52f5a28b0843aab">group</a> = j;</div>
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<div class="line"><span class="lineno"> 211</span> }</div>
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<div class="line"><span class="lineno"> 212</span> }</div>
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<div class="line"><span class="lineno"> 213</span> <span class="keywordflow">return</span> clusters;</div>
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<div class="line"><span class="lineno"> 214</span>}</div>
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<div class="ttc" id="agroup__k__means_html_gad339c41d3ee9e6729aca9e9ab3f7d2d9"><div class="ttname"><a href="../../d8/d71/group__k__means.html#gad339c41d3ee9e6729aca9e9ab3f7d2d9">calculateNearst</a></div><div class="ttdeci">int calculateNearst(observation *o, cluster clusters[], int k)</div><div class="ttdef"><b>Definition</b> k_means_clustering.c:69</div></div>
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<div class="ttc" id="agroup__k__means_html_gadee39a3f17bf5144df5592e48dbfc9f7"><div class="ttname"><a href="../../d8/d71/group__k__means.html#gadee39a3f17bf5144df5592e48dbfc9f7">calculateCentroid</a></div><div class="ttdeci">void calculateCentroid(observation observations[], size_t size, cluster *centroid)</div><div class="ttdef"><b>Definition</b> k_means_clustering.c:97</div></div>
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<div class="ttc" id="amalloc__dbg_8h_html_a725f50ecaf1959d96de79b36b4788fee"><div class="ttname"><a href="../../d2/ddd/malloc__dbg_8h.html#a725f50ecaf1959d96de79b36b4788fee">malloc</a></div><div class="ttdeci">#define malloc(bytes)</div><div class="ttdoc">This macro replace the standard malloc function with malloc_dbg.</div><div class="ttdef"><b>Definition</b> malloc_dbg.h:18</div></div>
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<div class="ttc" id="astructcluster_html"><div class="ttname"><a href="../../d1/d99/structcluster.html">cluster</a></div><div class="ttdef"><b>Definition</b> k_means_clustering.c:53</div></div>
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