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Authors: Mahdi Mohammadi 1 ; Saeed Adel Mehraban 2 ; Elnaz Bigdeli 1 ; Bijan Raahemi 1 and Ahmad Akbari 2

Affiliations: 1 University of Ottawa, Canada ; 2 Iran University of science and technology, Iran, Islamic Republic of

Keyword(s): Graph-based Classifier, Noisy Samples, Relational Data.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Clustering and Classification Methods ; Computational Intelligence ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems

Abstract: In this paper, we propose a non-parametric and noise resilient graph-based classification algorithm. In designing the proposed method, we represent each class of dataset as a set of sub-graphs. The main part of the training phase is how to build the classification graph based on the non-parametric k-associated optimal graph algorithm which is an extension of the parametric k-associated graph algorithm. In this paper, we propose a new extension and modification of the training phase of the k-associated optimal graph algorithm. We compare the modified version of the k-associated optimal graph (MKAOG) algorithm with the original k-associated optimal graph algorithm (KAOG). The experimental results demonstrate superior performance of our proposed method in the presence of different levels of noise on various datasets from the UCI repository.

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Paper citation in several formats:
Mohammadi, M.; Adel Mehraban, S.; Bigdeli, E.; Raahemi, B. and Akbari, A. (2014). A Noise Resilient and Non-parametric Graph-based Classifier. In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2014) - KDIR; ISBN 978-989-758-048-2; ISSN 2184-3228, SciTePress, pages 170-175. DOI: 10.5220/0005051801700175

@conference{kdir14,
author={Mahdi Mohammadi. and Saeed {Adel Mehraban}. and Elnaz Bigdeli. and Bijan Raahemi. and Ahmad Akbari.},
title={A Noise Resilient and Non-parametric Graph-based Classifier},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2014) - KDIR},
year={2014},
pages={170-175},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005051801700175},
isbn={978-989-758-048-2},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2014) - KDIR
TI - A Noise Resilient and Non-parametric Graph-based Classifier
SN - 978-989-758-048-2
IS - 2184-3228
AU - Mohammadi, M.
AU - Adel Mehraban, S.
AU - Bigdeli, E.
AU - Raahemi, B.
AU - Akbari, A.
PY - 2014
SP - 170
EP - 175
DO - 10.5220/0005051801700175
PB - SciTePress

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