Breast Cancer Detection with Reduced Feature Set
Joint Authors
Akan, Aydin
Mert, Ahmet
Bilgili, Erdem
Kilic, Niyazi
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-05-19
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
This paper explores feature reduction properties of independent component analysis (ICA) on breast cancer decision support system.
Wisconsin diagnostic breast cancer (WDBC) dataset is reduced to one-dimensional feature vector computing an independent component (IC).
The original data with 30 features and reduced one feature (IC) are used to evaluate diagnostic accuracy of the classifiers such as k-nearest neighbor (k-NN), artificial neural network (ANN), radial basis function neural network (RBFNN), and support vector machine (SVM).
The comparison of the proposed classification using the IC with original feature set is also tested on different validation (5/10-fold cross-validations) and partitioning (20%–40%) methods.
These classifiers are evaluated how to effectively categorize tumors as benign and malignant in terms of specificity, sensitivity, accuracy, F-score, Youden’s index, discriminant power, and the receiver operating characteristic (ROC) curve with its criterion values including area under curve (AUC) and 95% confidential interval (CI).
This represents an improvement in diagnostic decision support system, while reducing computational complexity.
American Psychological Association (APA)
Mert, Ahmet& Kilic, Niyazi& Bilgili, Erdem& Akan, Aydin. 2015. Breast Cancer Detection with Reduced Feature Set. Computational and Mathematical Methods in Medicine،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1057847
Modern Language Association (MLA)
Mert, Ahmet…[et al.]. Breast Cancer Detection with Reduced Feature Set. Computational and Mathematical Methods in Medicine No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1057847
American Medical Association (AMA)
Mert, Ahmet& Kilic, Niyazi& Bilgili, Erdem& Akan, Aydin. Breast Cancer Detection with Reduced Feature Set. Computational and Mathematical Methods in Medicine. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1057847
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057847