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<h2 title="Class LabelPropagation" class="title">Class LabelPropagation</h2>
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<pre>public class <span class="strong">LabelPropagation</span>
extends java.lang.Object</pre>
<div class="block">Label Propagation algorithm.</div>
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<td class="colOne"><code><strong><a href="../../../../../org/apache/spark/graphx/lib/LabelPropagation.html#LabelPropagation()">LabelPropagation</a></strong>()</code> </td>
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<td class="colFirst"><code>static <VD,ED> <a href="../../../../../org/apache/spark/graphx/Graph.html" title="class in org.apache.spark.graphx">Graph</a><java.lang.Object,ED></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/graphx/lib/LabelPropagation.html#run(org.apache.spark.graphx.Graph, int, scala.reflect.ClassTag)">run</a></strong>(<a href="../../../../../org/apache/spark/graphx/Graph.html" title="class in org.apache.spark.graphx">Graph</a><VD,ED> graph,
int maxSteps,
scala.reflect.ClassTag<ED> evidence$1)</code>
<div class="block">Run static Label Propagation for detecting communities in networks.</div>
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<h4>LabelPropagation</h4>
<pre>public LabelPropagation()</pre>
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<h4>run</h4>
<pre>public static <VD,ED> <a href="../../../../../org/apache/spark/graphx/Graph.html" title="class in org.apache.spark.graphx">Graph</a><java.lang.Object,ED> run(<a href="../../../../../org/apache/spark/graphx/Graph.html" title="class in org.apache.spark.graphx">Graph</a><VD,ED> graph,
int maxSteps,
scala.reflect.ClassTag<ED> evidence$1)</pre>
<div class="block">Run static Label Propagation for detecting communities in networks.
<p>
Each node in the network is initially assigned to its own community. At every superstep, nodes
send their community affiliation to all neighbors and update their state to the mode community
affiliation of incoming messages.
<p>
LPA is a standard community detection algorithm for graphs. It is very inexpensive
computationally, although (1) convergence is not guaranteed and (2) one can end up with
trivial solutions (all nodes are identified into a single community).
<p></div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>graph</code> - the graph for which to compute the community affiliation</dd><dd><code>maxSteps</code> - the number of supersteps of LPA to be performed. Because this is a static
implementation, the algorithm will run for exactly this many supersteps.
<p></dd><dd><code>evidence$1</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>a graph with vertex attributes containing the label of community affiliation</dd></dl>
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