📄 nnegativenodes.java
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/* Copyright (C) 2002 Univ. of Massachusetts Amherst, Computer Science Dept. This file is part of "MALLET" (MAchine Learning for LanguagE Toolkit). http://www.cs.umass.edu/~mccallum/mallet This software is provided under the terms of the Common Public License, version 1.0, as published by http://www.opensource.org. For further information, see the file `LICENSE' included with this distribution. */package edu.umass.cs.mallet.projects.seg_plus_coref.condclust.pipe;import edu.umass.cs.mallet.projects.seg_plus_coref.condclust.types.*;import edu.umass.cs.mallet.projects.seg_plus_coref.coreference.*;import edu.umass.cs.mallet.base.types.*;import edu.umass.cs.mallet.base.util.*;import edu.umass.cs.mallet.base.classify.*;import edu.umass.cs.mallet.base.pipe.*;import java.util.*;/** Feature is true if there exist at least N nodes in Cluster that * have a negative edge weight with Node*/public class NNegativeNodes extends Pipe{ /** Determines distance between two nodes*/ Classifier classifier; /** number of negative nodes we must see for this feature to fire */ int n; public NNegativeNodes (Classifier _classifier, int _n) { this.classifier = _classifier; this.n = _n; } public NNegativeNodes (Classifier _classifier) { this (_classifier, 1); } public Instance pipe (Instance carrier) { NodeClusterPair pair = (NodeClusterPair)carrier.getData(); Citation node = (Citation)pair.getNode(); Collection cluster = (Collection)pair.getCluster(); Iterator iter = cluster.iterator (); int numNeg = 0; while (iter.hasNext()) { Citation c = (Citation) iter.next(); NodePair np = new NodePair (c, node); Instance inst = new Instance (np, "unknown", null, np, classifier.getInstancePipe()); Labeling labeling = classifier.classify (inst).getLabeling(); if (labeling.labelAtLocation(0).toString().equals("no")) { if (++numNeg >= n) break; } } if (numNeg >= n) pair.setFeatureValue ("ClusterContainsAtLeast"+n+"NegativeNodes", 1.0); return carrier; }}
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