AIMC Topic: Support Vector Machine

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Maximum margin semi-supervised learning with irrelevant data.

Neural networks : the official journal of the International Neural Network Society Jul 15, 2015
Semi-supervised learning (SSL) is a typical learning paradigms training a model from both labeled and unlabeled data. The traditional SSL models usually assume unlabeled data are relevant to the labeled data, i.e., following the same distributions of...
Artificial Intelligence Supervised Machine Learning Support Vector Machine Entropy Data Interpretation, Statistical Models, Neurological Algorithms Models, Statistical Image Processing, Computer-Assisted
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Multiple Sparse Representations Classification.

PloS one Jul 15, 2015
Sparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dicti...
Magnetic Resonance Imaging Artificial Intelligence Principal Component Analysis Carotid Arteries Radiography Image Processing, Computer-Assisted Support Vector Machine
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Multiple kernel learning with random effects for predicting longitudinal outcomes and data integration.

Biometrics Jul 14, 2015
Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although, kernel-based st...
Machine Learning Algorithms Computer Simulation Humans Models, Statistical Alzheimer Disease Biometry Support Vector Machine Longitudinal Studies Disease Progression Statistics, Nonparametric Huntington Disease
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Quantitative Regression Models for the Prediction of Chemical Properties by an Efficient Workflow.

Molecular informatics Jul 14, 2015
Rapid safety assessment is more and more needed for the increasing chemicals both in chemical industries and regulators around the world. The traditional experimental methods couldn't meet the current demand any more. With the development of the info...
Tetrahymena pyriformis Support Vector Machine Models, Biological Computer Simulation Databases, Chemical
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Extracting biomedical events from pairs of text entities.

BMC bioinformatics Jul 13, 2015
BACKGROUND: Huge amounts of electronic biomedical documents, such as molecular biology reports or genomic papers are generated daily. Nowadays, these documents are mainly available in the form of unstructured free texts, which require heavy processin...
Support Vector Machine Natural Language Processing Data Mining Knowledge Bases Biomedical Research Humans Computational Biology Databases, Factual Models, Theoretical
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Binding Activity Prediction of Cyclin-Dependent Inhibitors.

Journal of chemical information and modeling Jul 10, 2015
The Cyclin-Dependent Kinases (CDKs) are the core components coordinating eukaryotic cell division cycle. Generally the crystal structure of CDKs provides information on possible molecular mechanisms of ligand binding. However, reliable and robust est...
Protein Binding Support Vector Machine Decision Trees Machine Learning Algorithms Protein Kinase Inhibitors Chromosomes Cyclin-Dependent Kinases Models, Molecular Bayes Theorem Protein Conformation
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Optimal combination of feature selection and classification via local hyperplane based learning strategy.

BMC bioinformatics Jul 10, 2015
BACKGROUND: Classifying cancers by gene selection is among the most important and challenging procedures in biomedicine. A major challenge is to design an effective method that eliminates irrelevant, redundant, or noisy genes from the classification,...
Gene Expression Profiling Gene Regulatory Networks Cluster Analysis Discriminant Analysis Support Vector Machine Humans Machine Learning Neoplasms
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Exploring supervised neighborhood preserving embedding (SNPE) as a nonlinear feature extraction method for vibrational spectroscopic discrimination of agricultural samples according to geographical origins.

Talanta Jul 9, 2015
Supervised neighborhood preserving embedding (SNPE), a nonlinear dimensionality reduction method, was employed to represent near-infrared (NIR) and Raman spectral features of agricultural samples (Angelica gigas, sesame, and red pepper), and the newl...
Sesamum Angelica Capsicum Geography Agriculture Spectrum Analysis, Raman Support Vector Machine Spectroscopy, Near-Infrared
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Near-Bayesian Support Vector Machines for imbalanced data classification with equal or unequal misclassification costs.

Neural networks : the official journal of the International Neural Network Society Jul 8, 2015
Support Vector Machines (SVMs) form a family of popular classifier algorithms originally developed to solve two-class classification problems. However, SVMs are likely to perform poorly in situations with data imbalance between the classes, particula...
Datasets as Topic Bayes Theorem Artifacts Support Vector Machine Data Interpretation, Statistical Algorithms
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Multistage virtual screening and identification of novel HIV-1 protease inhibitors by integrating SVM, shape, pharmacophore and docking methods.

European journal of medicinal chemistry Jul 6, 2015
The HIV-1 protease has proven to be a crucial component of the HIV replication machinery and a reliable target for anti-HIV drug discovery. In this study, we applied an optimized hierarchical multistage virtual screening method targeting HIV-1 protea...
HIV Protease Inhibitors Dose-Response Relationship, Drug Structure-Activity Relationship Drug Evaluation, Preclinical HIV Protease Molecular Structure Molecular Docking Simulation Support Vector Machine
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