Faye, I. (2012) A random feature selection method for classification of mammogram images. In: UNSPECIFIED.
Full text not available from this repository.Abstract
This article discusses the use of a random feature selection method for classification of mammogram images using a multi-scale transform. Each image is represented by a vector of coefficients. Subsets of columns are randomly generated and used for classification of a training set. The subsets achieving a predefined performance are kept and pooled in a final set for testing. The method is tested using a set of images provided by the Mammography Image Analysis Society (MIAS) to differentiate normal and abnormal images. In our experiments the classifiers K nearest neighbors (kNN) and Discriminant Analysis (DA) are used with Wavelet transform. © 2012 IEEE.
Item Type: | Conference or Workshop Item (UNSPECIFIED) |
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Additional Information: | cited By 4; Conference of 3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012 ; Conference Date: 8 February 2012 Through 10 February 2012; Conference Code:89401 |
Uncontrolled Keywords: | Feature selection methods; K-nearest neighbors; Multiscale transforms; Multiscales; Training sets, Discriminant analysis; Feature extraction; Intelligent systems; Mammography, X ray screens |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 09 Nov 2023 15:51 |
Last Modified: | 09 Nov 2023 15:51 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/3019 |