AIMC Topic: Support Vector Machine

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Cross-validation of matching correlation analysis by resampling matching weights.

Neural networks : the official journal of the International Neural Network Society
The strength of association between a pair of data vectors is represented by a nonnegative real number, called matching weight. For dimensionality reduction, we consider a linear transformation of data vectors, and define a matching error as the weig...

Enhanced Classification of Interstitial Lung Disease Patterns in HRCT Images Using Differential Lacunarity.

BioMed research international
The analysis and interpretation of high-resolution computed tomography (HRCT) images of the chest in the presence of interstitial lung disease (ILD) is a time-consuming task which requires experience. In this paper, a computer-aided diagnosis (CAD) s...

Multiclass Posterior Probability Twin SVM for Motor Imagery EEG Classification.

Computational intelligence and neuroscience
Motor imagery electroencephalography is widely used in the brain-computer interface systems. Due to inherent characteristics of electroencephalography signals, accurate and real-time multiclass classification is always challenging. In order to solve ...

Discovery of Influenza A virus neuraminidase inhibitors using support vector machine and Naïve Bayesian models.

Molecular diversity
Neuraminidase (NA) is a critical enzyme in the life cycle of influenza virus, which is known as a successful paradigm in the design of anti-influenza agents. However, to date there are no classification models for the virtual screening of NA inhibito...

Computational identification of piRNA targets on mouse mRNAs.

Bioinformatics (Oxford, England)
MOTIVATION: PIWI-interacting RNAs (piRNAs) are a class of small non-coding RNAs that are highly abundant in the germline. One important role of piRNAs is to defend genome integrity by guiding PIWI proteins to silence transposable elements (TEs), whic...

In-Vivo Imaging of Cell Migration Using Contrast Enhanced MRI and SVM Based Post-Processing.

PloS one
The migration of cells within a living organism can be observed with magnetic resonance imaging (MRI) in combination with iron oxide nanoparticles as an intracellular contrast agent. This method, however, suffers from low sensitivity and specificty. ...

Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offenders.

NeuroImage
Classification models are becoming useful tools for finding patterns in neuroimaging data sets that are not observable to the naked eye. Many of these models are applied to discriminating clinical groups such as schizophrenic patients from healthy co...

Classification of first-episode psychosis in a large cohort of patients using support vector machine and multiple kernel learning techniques.

NeuroImage
First episode psychosis (FEP) patients are of particular interest for neuroimaging investigations because of the absence of confounding effects due to medications and chronicity. Nonetheless, imaging data are prone to heterogeneity because for exampl...

NBSPred: a support vector machine-based high-throughput pipeline for plant resistance protein NBSLRR prediction.

Bioinformatics (Oxford, England)
UNLABELLED: The nucleotide binding site leucine-rich repeats (NBSLRRs) belong to one of the largest known families of disease resistance genes that encode resistance proteins (R-protein) against the pathogens of plants. Various defence mechanisms hav...

Characterizing informative sequence descriptors and predicting binding affinities of heterodimeric protein complexes.

BMC bioinformatics
BACKGROUND: Protein-protein interactions (PPIs) are involved in various biological processes, and underlying mechanism of the interactions plays a crucial role in therapeutics and protein engineering. Most machine learning approaches have been develo...