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Added normalized mutual information evaluation for clustering.
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| /* | ||
| * This program is free software; you can redistribute it and/or modify | ||
| * it under the terms of the GNU General Public License as published by | ||
| * the Free Software Foundation; either version 3 of the License, or | ||
| * (at your option) any later version. | ||
| * | ||
| * Written (W) 2012 Chiyuan Zhang | ||
| * Copyright (C) 2012 Chiyuan Zhang | ||
| */ | ||
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| #ifndef __CLUSTERINGMUTUALINFORMATION_H__ | ||
| #define __CLUSTERINGMUTUALINFORMATION_H__ | ||
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| #include <vector> | ||
| #include <cmath> | ||
| #include <algorithm> | ||
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| #include <shogun/evaluation/ClusteringEvaluation.h> | ||
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| namespace shogun | ||
| { | ||
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| /** @brief clustering (normalized) mutual information | ||
| */ | ||
| class CClusteringMutualInformation: public CClusteringEvaluation | ||
| { | ||
| public: | ||
| /** constructor */ | ||
| CClusteringMutualInformation(): CClusteringEvaluation() {} | ||
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| /** destructor */ | ||
| virtual ~CClusteringMutualInformation() {} | ||
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| /** evaluate labels | ||
| * Make sure to call CClusteringEvaluation::best_map to map the predicted label | ||
| * before calculating mutual information. | ||
| * | ||
| * @param predicted labels for evaluating | ||
| * @param ground_truth labels assumed to be correct | ||
| * @return evaluation result | ||
| */ | ||
| virtual float64_t evaluate(CLabels* predicted, CLabels* ground_truth) | ||
| { | ||
| std::vector<int32_t> label_p=unique_labels(predicted); | ||
| std::vector<int32_t> label_g=unique_labels(ground_truth); | ||
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| if (label_p.size() != label_g.size()) | ||
| SG_ERROR("Number of classes are different\n"); | ||
| uint32_t n_class=label_p.size(); | ||
| float64_t n_label=predicted->get_num_labels(); | ||
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| SGVector<int32_t> ilabels_p=predicted->get_int_labels(); | ||
| SGVector<int32_t> ilabels_g=ground_truth->get_int_labels(); | ||
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| SGMatrix<float64_t> G(n_class, n_class); | ||
| for (size_t i=0; i < n_class; ++i) | ||
| for (size_t j=0; j < n_class; ++j) | ||
| G(i, j)=find_match_count(ilabels_g, label_g[i], | ||
| ilabels_p, label_p[j])/n_label; | ||
| std::vector<float64_t> G_rowsum(n_class), G_colsum(n_class); | ||
| for (size_t i=0; i < n_class; ++i) | ||
| { | ||
| for (size_t j=0; j < n_class; ++j) | ||
| { | ||
| G_rowsum[i] += G(i, j); | ||
| G_colsum[i] += G(j, i); | ||
| } | ||
| } | ||
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| float64_t mutual_info = 0; | ||
| for (size_t i=0; i < n_class; ++i) | ||
| { | ||
| for (size_t j=0; j < n_class; ++j) | ||
| { | ||
| if (G(i, j) != 0) | ||
| mutual_info += G(i, j) * log(G(i,j) / | ||
| (G_rowsum[i]*G_colsum[j]))/log(2.); | ||
| } | ||
| } | ||
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| float64_t entropy_p = 0, entropy_g = 0; | ||
| for (size_t i=0; i < n_class; ++i) | ||
| { | ||
| entropy_g += -G_rowsum[i] * log(G_rowsum[i])/log(2.); | ||
| entropy_p += -G_colsum[i] * log(G_colsum[i])/log(2.); | ||
| } | ||
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| return mutual_info / std::max(entropy_g, entropy_p); | ||
| } | ||
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| /** @return whether criterium has to be maximized or minimized */ | ||
| virtual EEvaluationDirection get_evaluation_direction() | ||
| { | ||
| return ED_MINIMIZE; | ||
| } | ||
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| /** Returns the name of the SGSerializable instance. It MUST BE | ||
| * the CLASS NAME without the prefixed `C'. | ||
| * | ||
| * @return name of the SGSerializable | ||
| */ | ||
| virtual const char* get_name() const | ||
| { | ||
| return "ClusteringMutualInformation"; | ||
| } | ||
| }; | ||
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| } | ||
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| #endif /* end of include guard: __CLUSTERINGMUTUALINFORMATION_H__ */ |