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- function score = CalculateInversePurity(true_clustering, test_clustering)
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- score = 0;
- num_clusters = max(true_clustering);
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- for i = 1 : num_clusters
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- clusters_for_current_label = test_clustering(true_clustering == i);
- majority = mode(clusters_for_current_label);
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- n = size(true_clustering, 1);
- union_size = sum(clusters_for_current_label == majority);
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- score = score + union_size * 1 / n;
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- end
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