AIMC Topic: Support Vector Machine

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Using support vector machines to identify protein phosphorylation sites in viruses.

Journal of molecular graphics & modelling
Phosphorylation of viral proteins plays important roles in enhancing replication and inhibition of normal host-cell functions. Given its importance in biology, a unique opportunity has arisen to identify viral protein phosphorylation sites. However, ...

Comparison of l₁-Norm SVR and Sparse Coding Algorithms for Linear Regression.

IEEE transactions on neural networks and learning systems
Support vector regression (SVR) is a popular function estimation technique based on Vapnik's concept of support vector machine. Among many variants, the l1-norm SVR is known to be good at selecting useful features when the features are redundant. Spa...

Development of electroencephalographic pattern classifiers for real and imaginary thumb and index finger movements of one hand.

Artificial intelligence in medicine
OBJECTIVE: This study aimed to find effective approaches to electroencephalographic (EEG) signal analysis and resolve problems of real and imaginary finger movement pattern recognition and categorization for one hand.

Online monitoring and control of particle size in the grinding process using least square support vector regression and resilient back propagation neural network.

ISA transactions
Particle size soft sensing in cement mills will be largely helpful in maintaining desired cement fineness or Blaine. Despite the growing use of vertical roller mills (VRM) for clinker grinding, very few research work is available on VRM modeling. Thi...

Kernel collaborative representation-based automatic seizure detection in intracranial EEG.

International journal of neural systems
Automatic seizure detection is of great significance in the monitoring and diagnosis of epilepsy. In this study, a novel method is proposed for automatic seizure detection in intracranial electroencephalogram (iEEG) recordings based on kernel collabo...

Classification of lung cancer using ensemble-based feature selection and machine learning methods.

Molecular bioSystems
Lung cancer is one of the leading causes of death worldwide. There are three major types of lung cancers, non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC) and carcinoid. NSCLC is further classified into lung adenocarcinoma (LADC), sq...

repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects.

Bioinformatics (Oxford, England)
UNLABELLED: In order to develop powerful computational predictors for identifying the biological features or attributes of DNAs, one of the most challenging problems is to find a suitable approach to effectively represent the DNA sequences. To facili...

Stable feature selection for clinical prediction: exploiting ICD tree structure using Tree-Lasso.

Journal of biomedical informatics
Modern healthcare is getting reshaped by growing Electronic Medical Records (EMR). Recently, these records have been shown of great value towards building clinical prediction models. In EMR data, patients' diseases and hospital interventions are capt...

A generic support vector machine model for preoperative glioma survival associations.

Radiology
PURPOSE: To develop a generic support vector machine (SVM) model by using magnetic resonance (MR) imaging-based blood volume distribution data for preoperative glioma survival associations and to prospectively evaluate the diagnostic effectiveness of...