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Electrical and Computer Engineering

Old Dominion University

Genetic algorithm

Publication Year

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Full-Text Articles in Engineering

An Improved Smote Algorithm Based On Genetic Algorithm For Imbalanced Data Collection, Qiong Gu, Xian-Ming Wang, Zhao Wu, Bing Ning, Chun-Sheng Xin Jan 2016

An Improved Smote Algorithm Based On Genetic Algorithm For Imbalanced Data Collection, Qiong Gu, Xian-Ming Wang, Zhao Wu, Bing Ning, Chun-Sheng Xin

Electrical & Computer Engineering Faculty Publications

Classification of imbalanced data has been recognized as a crucial problem in machine learning and data mining. In an imbalanced dataset, minority class instances are likely to be misclassified. When the synthetic minority over-sampling technique (SMOTE) is applied in imbalanced dataset classification, the same sampling rate is set for all samples of the minority class in the process of synthesizing new samples, this scenario involves blindness. To overcome this problem, an improved SMOTE algorithm based on genetic algorithm (GA), namely, GASMOTE was proposed. First, GASMOTE set different sampling rates for different minority class samples. A combination of the sampling rates …


Optimizing Computer-Aided Colonic Polyp Detection For Ct Colonography By Evolving The Pareto Front, Jiang Li, Adam Huang, Jack Tao, Jiamin Liu, Robert L. Van Uitert, Nicholas Petrick, Ronald Summers Jan 2009

Optimizing Computer-Aided Colonic Polyp Detection For Ct Colonography By Evolving The Pareto Front, Jiang Li, Adam Huang, Jack Tao, Jiamin Liu, Robert L. Van Uitert, Nicholas Petrick, Ronald Summers

Electrical & Computer Engineering Faculty Publications

A multiobjective genetic algorithm is designed to optimize a computer-aided detection (CAD) system for identifying colonic polyps. Colonic polyps appear as elliptical protrusions on the inner surface of the colon. Curvature-based features for colonic polyp detection have proved to be successful in several CT colonography (CTC) CAD systems. Our CTC CAD program uses a sequential classifier to form initial polyp detections on the colon surface. The classifier utilizes a set of thresholds on curvature-based features to cluster suspicious colon surface regions into polyp candidates. The thresholds were previously chosen experimentally by using feature histograms. The chosen thresholds were effective for …