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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.

CC BY-NC-ND 4.0

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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