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Intrusion detection in computer networks using optimum-path forest clustering
(2012-12-01)
Nowadays, organizations face the problem of keeping their information protected, available and trustworthy. In this context, machine learning techniques have also been extensively applied to this task. Since manual labeling ...
Intrusion detection in computer networks using optimum-path forest clustering
(2012-12-01)
Nowadays, organizations face the problem of keeping their information protected, available and trustworthy. In this context, machine learning techniques have also been extensively applied to this task. Since manual labeling ...
Electrical consumers data clustering through optimum-path forest
(2011-12-21)
Non-technical losses identification has been paramount in the last decade. Since we have datasets with hundreds of legal and illegal profiles, one may have a method to group data into subprofiles in order to minimize the ...
Electrical consumers data clustering through optimum-path forest
(2011-12-21)
Non-technical losses identification has been paramount in the last decade. Since we have datasets with hundreds of legal and illegal profiles, one may have a method to group data into subprofiles in order to minimize the ...
Pattern-based clustering using unsupervised decision trees
(Instituto Nacional de Astrofísica, Óptica y Electrónica, 2015)
Pattern-based clustering using unsupervised decision trees
(Instituto Nacional de Astrofísica, Óptica y Electrónica, 2015)
Clustering algorithm based on asymmetric similarity and paradigmatic features
(Inderscience Enterprises Ltd., 2016)
Similarity measures are essential to solve many pattern recognition problems such as classification, clustering, and information retrieval. Various similarity measures are categorised in both syntactic and semantic ...