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This paper studies on the predicted regression model of support vector machines (SVM). Aiming at the shortage that with the amount of samples grows, training time increases rapidly as well, we propose an optimization algorithm to optimize it for large scale dataset. The optimization algorithm is based on ensemble learning and dynamic clustering. Firstly, we use dynamic cluster method to generate different...
With the accelerating advancement of biomedical research, it has been widely accepted that genetic variation plays a critical role in the pathogenesis of human inherited diseases. As an important type of genetic variation, nonsynonymous single nucleotide polymorphisms (nsSNPs) that occur in protein coding regions lead to amino acid substitutions in proteins, affecting structures and functions of proteins,...
The combined use of gene expression profiles and protein-protein interaction (PPI) networks has recently shed light on breast cancer research by selecting a small number of subnetworks as disease markers and then using them for the classification of metastasis. Based on previously identified subnetwork markers, we compare three ensemble learning approaches (AdaBoost, LogitBoost and random forest)...
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