Warning: pg_query(): Query failed: ERROR: missing chunk number 0 for toast value 29512337 in pg_toast_2619 in /dati/webiit-old/includes/database.pgsql.inc on line 138 Warning: ERROR: missing chunk number 0 for toast value 29512337 in pg_toast_2619 query: SELECT data, created, headers, expire, serialized FROM cache_page WHERE cid = 'https://www-old.iit.cnr.it/node/40885' in /dati/webiit-old/includes/database.pgsql.inc on line 159 Warning: pg_query(): Query failed: ERROR: missing chunk number 0 for toast value 29512337 in pg_toast_2619 in /dati/webiit-old/includes/database.pgsql.inc on line 138 Warning: ERROR: missing chunk number 0 for toast value 29512337 in pg_toast_2619 query: SELECT data, created, headers, expire, serialized FROM cache_page WHERE cid = 'https://www-old.iit.cnr.it/node/40885' in /dati/webiit-old/includes/database.pgsql.inc on line 159 On the Abstraction of a Categorical Clustering Algorithm | IIT - CNR - Istituto di Informatica e Telematica
IIT Home Page CNR Home Page

On the Abstraction of a Categorical Clustering Algorithm

Despite being one of the most common approach in unsupervised data analysis, a very small literature exists on the formalization of clustering algorithms. This paper proposes a semiring-based methodology, named Feature-Cluster Algebra, which is applied to abstract the representation of a labeled tree structure representing a hierarchical categorical clustering algorithm, named CCTree. The elements of the feature-cluster algebra are called terms. We prove that a specific kind of a term, under some conditions, fully abstracts a labeled tree structure. The abstraction methodology maps the original problem to a new representation by removing unwanted details, which makes it simpler to handle. Moreover, we present a set of relations and functions on the algebraic structure to shape the requirements of a term to represent a CCTree structure. The proposed formal approach can be generalized to other categorical clustering (classification) algorithms in which features play key roles in specifying the clusters (classes).

Machine Learning and Data Mining in Pattern Recognition, New York, 2016

Autori esterni: Mohamed Mejri (Universite Laval), Nadia Tawbi (Universite Laval )
Autori IIT:

Mina Sheikhalishahi

Foto di Mina Sheikhalishahi

Tipo: Contributo in atti di convegno
Area di disciplina: Computer Science & Engineering

File: 1379.pdf

Attività: Architetture, protocolli e meccanismi di sicurezza per sistemi e servizi distribuiti