coco
98 lines
3.9 KiB
C++
98 lines
3.9 KiB
C++
// Copyright (C) 2012 Davis E. King (davis@dlib.net)
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// License: Boost Software License See LICENSE.txt for the full license.
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#undef DLIB_CHINESE_WHISPErS_ABSTRACT_Hh_
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#ifdef DLIB_CHINESE_WHISPErS_ABSTRACT_Hh_
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#include <vector>
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#include "../rand.h"
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#include "../graph_utils/ordered_sample_pair_abstract.h"
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#include "../graph_utils/sample_pair_abstract.h"
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namespace dlib
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{
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// ----------------------------------------------------------------------------------------
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unsigned long chinese_whispers (
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const std::vector<ordered_sample_pair>& edges,
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std::vector<unsigned long>& labels,
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const unsigned long num_iterations,
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dlib::rand& rnd
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);
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/*!
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requires
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- is_ordered_by_index(edges) == true
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ensures
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- This function implements the graph clustering algorithm described in the
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paper: Chinese Whispers - an Efficient Graph Clustering Algorithm and its
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Application to Natural Language Processing Problems by Chris Biemann.
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- Interprets edges as a directed graph. That is, it contains the edges on the
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said graph and the ordered_sample_pair::distance() values define the edge
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weights (larger values indicating a stronger edge connection between the
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nodes). If an edge has a distance() value of infinity then it is considered
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a "must link" edge.
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- returns the number of clusters found.
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- #labels.size() == max_index_plus_one(edges)
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- for all valid i:
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- #labels[i] == the cluster ID of the node with index i in the graph.
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- 0 <= #labels[i] < the number of clusters found
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(i.e. cluster IDs are assigned contiguously and start at 0)
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- Duplicate edges are interpreted as if there had been just one edge with a
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distance value equal to the sum of all the duplicate edge's distance values.
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- The algorithm performs exactly num_iterations passes over the graph before
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terminating.
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!*/
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// ----------------------------------------------------------------------------------------
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unsigned long chinese_whispers (
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const std::vector<sample_pair>& edges,
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std::vector<unsigned long>& labels,
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const unsigned long num_iterations,
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dlib::rand& rnd
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);
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/*!
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ensures
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- This function is identical to the above chinese_whispers() routine except
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that it operates on a vector of sample_pair objects instead of
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ordered_sample_pairs. Therefore, this is simply a convenience routine. In
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particular, it is implemented by transforming the given edges into
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ordered_sample_pairs and then calling the chinese_whispers() routine defined
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above.
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!*/
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// ----------------------------------------------------------------------------------------
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unsigned long chinese_whispers (
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const std::vector<ordered_sample_pair>& edges,
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std::vector<unsigned long>& labels,
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const unsigned long num_iterations = 100
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);
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/*!
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requires
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- is_ordered_by_index(edges) == true
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ensures
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- performs: return chinese_whispers(edges, labels, num_iterations, rnd)
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where rnd is a default initialized dlib::rand object.
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!*/
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// ----------------------------------------------------------------------------------------
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unsigned long chinese_whispers (
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const std::vector<sample_pair>& edges,
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std::vector<unsigned long>& labels,
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const unsigned long num_iterations = 100
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);
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/*!
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ensures
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- performs: return chinese_whispers(edges, labels, num_iterations, rnd)
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where rnd is a default initialized dlib::rand object.
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!*/
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// ----------------------------------------------------------------------------------------
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}
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#endif // DLIB_CHINESE_WHISPErS_ABSTRACT_Hh_
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