AIMC Topic: Support Vector Machine

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Protein-protein interaction inference based on semantic similarity of Gene Ontology terms.

Journal of theoretical biology
Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computational approaches have attracted more and more attentions from the biological community. The semantic si...

Novel risk index for the identification of age-related macular degeneration using radon transform and DWT features.

Computers in biology and medicine
Age-related Macular Degeneration (AMD) affects the central vision of aged people. It can be diagnosed due to the presence of drusen, Geographic Atrophy (GA) and Choroidal Neovascularization (CNV) in the fundus images. It is labor intensive and time-c...

A New Feature Vector Based on Gene Ontology Terms for Protein-Protein Interaction Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Protein-protein interaction (PPI) plays a key role in understanding cellular mechanisms in different organisms. Many supervised classifiers like Random Forest (RF) and Support Vector Machine (SVM) have been used for intra or inter-species interaction...

Use of machine learning to improve autism screening and diagnostic instruments: effectiveness, efficiency, and multi-instrument fusion.

Journal of child psychology and psychiatry, and allied disciplines
BACKGROUND: Machine learning (ML) provides novel opportunities for human behavior research and clinical translation, yet its application can have noted pitfalls (Bone et al., 2015). In this work, we fastidiously utilize ML to derive autism spectrum d...

gkmSVM: an R package for gapped-kmer SVM.

Bioinformatics (Oxford, England)
UNLABELLED: We present a new R package for training gapped-kmer SVM classifiers for DNA and protein sequences. We describe an improved algorithm for kernel matrix calculation that speeds run time by about 2 to 5-fold over our original gkmSVM algorith...

Automatic classification of 6-month-old infants at familial risk for language-based learning disorder using a support vector machine.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVES: This study assesses the ability of a novel, "automatic classification" approach to facilitate identification of infants at highest familial risk for language-learning disorders (LLD) and to provide converging assessments to enable earlier...

Improvements on ν-Twin Support Vector Machine.

Neural networks : the official journal of the International Neural Network Society
In this paper, we propose two novel binary classifiers termed as "Improvements on ν-Twin Support Vector Machine: Iν-TWSVM and Iν-TWSVM (Fast)" that are motivated by ν-Twin Support Vector Machine (ν-TWSVM). Similar to ν-TWSVM, Iν-TWSVM determines two ...

An Interactive Astronaut-Robot System with Gesture Control.

Computational intelligence and neuroscience
Human-robot interaction (HRI) plays an important role in future planetary exploration mission, where astronauts with extravehicular activities (EVA) have to communicate with robot assistants by speech-type or gesture-type user interfaces embedded in ...

Online Sequential Projection Vector Machine with Adaptive Data Mean Update.

Computational intelligence and neuroscience
We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one o...

The Virtual Screening of the Drug Protein with a Few Crystal Structures Based on the Adaboost-SVM.

Computational and mathematical methods in medicine
Using the theory of machine learning to assist the virtual screening (VS) has been an effective plan. However, the quality of the training set may reduce because of mixing with the wrong docking poses and it will affect the screening efficiencies. To...