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An Efficient Optimization Method for Solving Unsupervised Data Classification Problems
المؤلفون المشاركون
Shabanzadeh, Parvaneh
Yusof, Rubiyah
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-07-29
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
Unsupervised data classification (or clustering) analysis is one of the most useful tools and a descriptive task in data mining that seeks to classify homogeneous groups of objects based on similarity and is used in many medical disciplines and various applications.
In general, there is no single algorithm that is suitable for all types of data, conditions, and applications.
Each algorithm has its own advantages, limitations, and deficiencies.
Hence, research for novel and effective approaches for unsupervised data classification is still active.
In this paper a heuristic algorithm, Biogeography-Based Optimization (BBO) algorithm, was adapted for data clustering problems by modifying the main operators of BBO algorithm, which is inspired from the natural biogeography distribution of different species.
Similar to other population-based algorithms, BBO algorithm starts with an initial population of candidate solutions to an optimization problem and an objective function that is calculated for them.
To evaluate the performance of the proposed algorithm assessment was carried on six medical and real life datasets and was compared with eight well known and recent unsupervised data classification algorithms.
Numerical results demonstrate that the proposed evolutionary optimization algorithm is efficient for unsupervised data classification.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Shabanzadeh, Parvaneh& Yusof, Rubiyah. 2015. An Efficient Optimization Method for Solving Unsupervised Data Classification Problems. Computational and Mathematical Methods in Medicine،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1058002
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Shabanzadeh, Parvaneh& Yusof, Rubiyah. An Efficient Optimization Method for Solving Unsupervised Data Classification Problems. Computational and Mathematical Methods in Medicine No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1058002
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Shabanzadeh, Parvaneh& Yusof, Rubiyah. An Efficient Optimization Method for Solving Unsupervised Data Classification Problems. Computational and Mathematical Methods in Medicine. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1058002
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1058002
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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