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Full-Text Articles in Physical Sciences and Mathematics
Machine Learning And Graph Theory Approaches For Classification And Prediction Of Protein Structure, Gulsah Altun
Machine Learning And Graph Theory Approaches For Classification And Prediction Of Protein Structure, Gulsah Altun
Computer Science Dissertations
Recently, many methods have been proposed for the classification and prediction problems in bioinformatics. One of these problems is the protein structure prediction. Machine learning approaches and new algorithms have been proposed to solve this problem. Among the machine learning approaches, Support Vector Machines (SVM) have attracted a lot of attention due to their high prediction accuracy. Since protein data consists of sequence and structural information, another most widely used approach for modeling this structured data is to use graphs. In computer science, graph theory has been widely studied; however it has only been recently applied to bioinformatics. In this …
Improving Feature Selection Techniques For Machine Learning, Feng Tan
Improving Feature Selection Techniques For Machine Learning, Feng Tan
Computer Science Dissertations
As a commonly used technique in data preprocessing for machine learning, feature selection identifies important features and removes irrelevant, redundant or noise features to reduce the dimensionality of feature space. It improves efficiency, accuracy and comprehensibility of the models built by learning algorithms. Feature selection techniques have been widely employed in a variety of applications, such as genomic analysis, information retrieval, and text categorization. Researchers have introduced many feature selection algorithms with different selection criteria. However, it has been discovered that no single criterion is best for all applications. We proposed a hybrid feature selection framework called based on genetic …