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A Comparative Study of Statistical and Artificial Intelligence based Classification Algorithms on Central Nervous System Cancer Microarray Gene Expression Data
Date
2016-09-01
Author
Arslan, Mustafa Turan
Kalınlı, Adem
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https://hdl.handle.net/11511/78226
Journal
International Journal of Intelligent Systems and Applications in Engineering
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A Comparative Study of Statistical and Artificial Intelligence based Classification Algorithms on Central Nervous System Cancer Microarray Gene Expression Data
Arslan, Mustafa Turan; Kalınlı, Adem (2016-09-03)
A variety of methods are used in order to classify cancer gene expression profiles based on microarray data. Especially, statistical methods such as Support Vector Machines (SVM), Decision Trees (DT) and Bayes are widely preferred to classify on microarray cancer data. However, the statistical methods can often be inadequate to solve problems which are based on particularly large-scale data such as DNA microarray data. Therefore, artificial intelligence-based methods have been used to classify on microarray...
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Karancı, Hüseyin; Sönmez, Rifat; Department of Civil Engineering (2010)
Construction cost estimating is essential for all of the stakeholders of a construction project from the beginning stage to the end. At early stages of a construction project, the design information and scope definition are very limited, hence; during conceptual (early) cost estimation, achieving high accuracy is very difficult. The level of uncertainty included in the cost estimations should be emphasized for making correct decisions throughout the dynamic stages of construction project management process,...
A comparative study of anisotropic hyperelastic models of biological soft tissues
Açan, Alp Kağan; Dal, Hüsnü; Department of Mechanical Engineering (2021-8)
In the last two decades, there has been significant growth of interest in the mechanical behavior of biological soft tissues approached from the continuum mechanical perspective. A plenty of constitutive models have been proposed that represent the anisotropic hyperelastic behavior of biological soft tissues. Generally, invariant and fiber dispersion-based models are two main categories considered during the modeling steps. Among the anisotropic models, fiber dispersion-based constitutive models are known t...
A comparative study on ILP-based concept discovery systems
Kavurucu, Yusuf; Karagöz, Pınar; Toroslu, İsmail Hakkı (2011-09-01)
Inductive Logic Programming (ILP) studies learning from examples, within the framework provided by clausal logic. ILP has become a popular subject in the field of data mining due to its ability to discover patterns in relational domains. Several ILP-based concept discovery systems are developed which employs various search strategies, heuristics and language pattern limitations. LINUS, GOLEM, CIGOL, MIS, FOIL, PROGOL, ALEPH and WARMR are well-known ILP-based systems. In this work, firstly introductory infor...
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Badienia, Yashar; Dal, Hüsnü; Department of Mechanical Engineering (2019)
Hyperelastic materials are widely used over the last decades. Studies on molecular structure and stress-stretch response of such materials goes back to 1940. Since then, many researchers have developed various material models to represent the response of hyperelastic materials undergoing different loading scenarios. Generally phenomenological and micromechanically based material models are the two main categories considered during the modeling steps. Among the hyperelastic material models micromechanically ...
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M. T. Arslan and A. Kalınlı, “A Comparative Study of Statistical and Artificial Intelligence based Classification Algorithms on Central Nervous System Cancer Microarray Gene Expression Data,”
International Journal of Intelligent Systems and Applications in Engineering
, pp. 78–81, 2016, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/78226.