cdlib.evaluation.purity¶
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purity
(communities: object) → cdlib.evaluation.fitness.FitnessResult¶ Purity is the product of the frequencies of the most frequent labels carried by the nodes within the communities
Parameters: communities – AttrNodeClustering object Returns: FitnessResult object Example:
>>> from cdlib.algorithms import eva >>> from cdlib import evaluation >>> import random >>> l1 = ['A', 'B', 'C', 'D'] >>> l2 = ["E", "F", "G"] >>> g = nx.barabasi_albert_graph(100, 5) >>> labels=dict() >>> for node in g.nodes(): >>> labels[node]={"l1":random.choice(l1), "l2":random.choice(l2)} >>> communities = eva(g_attr, labels, alpha=0.5) >>> pur = evaluation.purity(communities)
References: - Citraro, Salvatore, and Giulio Rossetti. “Eva: Attribute-Aware Network Segmentation.” International Conference on Complex Networks and Their Applications. Springer, Cham, 2019.