Breast Cancer Classification by Artificial Immune Algorithm based Validity Interval Cells Selection

Rima Daoudi; Khalifa Djemal

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Paper

Breast Cancer Classification by Artificial Immune Algorithm based Validity Interval Cells Selection

Topics: Bio-Inspired Hardware and Networks; Evolution Strategies; Evolutionary Multiobjective Optimization; Genetic Algorithms; Genetic Programming; Machine Learning

In Proceedings of the 8th International Joint Conference on Computational Intelligence - Volume 0IJCCI, 209-216, 2016 , Porto, Portugal

Authors: Rima Daoudi and Khalifa Djemal

Affiliation: IBISC Laboratory and Evry Val dEssonne University, France

Keyword(s): Breast Cancer, Classification, Artificial Immune System, Validity Interval.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Bio-inspired Hardware and Networks ; Computational Intelligence ; Evolution Strategies ; Evolutionary Computing ; Evolutionary Multiobjective Optimization ; Genetic Algorithms ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems

Abstract: We present in this work an Artificial Immune System (AIS) algorithm for breast cancer classification and diagnosis. The main contribution is to select memory cells according to their belonging to a validity interval based on average similarity of training cells. The behaviour of these created memory cells preserves the diversity of original cancer learning class. All these operations allow to generate a set of memory cells with a global representativeness of the database which enables breast cancer classification and recognition. Promising results have been obtained on both Wisconsin Diagnosis Breast Cancer Database (WDBC) and (DDSM) Digital Database for Screening Mammography.

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Paper citation in several formats:

Daoudi, R. and Djemal, K. (2016). Breast Cancer Classification by Artificial Immune Algorithm based Validity Interval Cells Selection. In Proceedings of the 8th International Joint Conference on Computational Intelligence (IJCCI 2016) - ECTA; ISBN 978-989-758-201-1, SciTePress, pages 209-216. DOI: 10.5220/0006057202090216

@conference{ecta16,
author={Rima Daoudi. and Khalifa Djemal.},
title={Breast Cancer Classification by Artificial Immune Algorithm based Validity Interval Cells Selection},
booktitle={Proceedings of the 8th International Joint Conference on Computational Intelligence (IJCCI 2016) - ECTA},
year={2016},
pages={209-216},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006057202090216},
isbn={978-989-758-201-1},
}

TY - CONF

JO - Proceedings of the 8th International Joint Conference on Computational Intelligence (IJCCI 2016) - ECTA
TI - Breast Cancer Classification by Artificial Immune Algorithm based Validity Interval Cells Selection
SN - 978-989-758-201-1
AU - Daoudi, R.
AU - Djemal, K.
PY - 2016
SP - 209
EP - 216
DO - 10.5220/0006057202090216
PB - SciTePress