Search results for " high dimensional"

showing 4 items of 4 documents

LogDet divergence-based metric learning with triplet constraints and its applications.

2014

How to select and weigh features has always been a difficult problem in many image processing and pattern recognition applications. A data-dependent distance measure can address this problem to a certain extent, and therefore an accurate and efficient metric learning becomes necessary. In this paper, we propose a LogDet divergence-based metric learning with triplet constraints (LDMLT) approach, which can learn Mahalanobis distance metric accurately and efficiently. First of all, we demonstrate the good properties of triplet constraints and apply it in LogDet divergence-based metric learning model. Then, to deal with high-dimensional data, we apply a compressed representation method to learn…

AutomatedData InterpretationBiometryFeature extractionhigh dimensional datametric learningPattern RecognitionFacial recognition systemSensitivity and SpecificityMatrix decompositionPattern Recognition Automatedcompressed representationComputer-AssistedArtificial Intelligencecompressed representation; high dimensional data; LogDet divergence; metric learning; triplet constraint; Artificial Intelligence; Biometry; Data Interpretation Statistical; Face; Humans; Image Enhancement; Image Interpretation Computer-Assisted; Pattern Recognition Automated; Photography; Reproducibility of Results; Sensitivity and Specificity; Algorithms; Facial Expression; Software; Medicine (all); Computer Graphics and Computer-Aided DesignImage Interpretation Computer-AssistedPhotographyHumansDivergence (statistics)Image retrievalImage InterpretationMathematicsMahalanobis distancebusiness.industryLogDet divergenceMedicine (all)Reproducibility of ResultsPattern recognitionStatisticalImage EnhancementComputer Graphics and Computer-Aided DesignFacial ExpressionComputingMethodologies_PATTERNRECOGNITIONComputer Science::Computer Vision and Pattern RecognitionData Interpretation StatisticalFaceMetric (mathematics)Pattern recognition (psychology)Artificial intelligencetriplet constraintbusinessSoftwareAlgorithmsIEEE transactions on image processing : a publication of the IEEE Signal Processing Society
researchProduct

Variability of Classification Results in Data with High Dimensionality and Small Sample Size

2021

The study focuses on the analysis of biological data containing information on the number of genome sequences of intestinal microbiome bacteria before and after antibiotic use. The data have high dimensionality (bacterial taxa) and a small number of records, which is typical of bioinformatics data. Classification models induced on data sets like this usually are not stable and the accuracy metrics have high variance. The aim of the study is to create a preprocessing workflow and a classification model that can perform the most accurate classification of the microbiome into groups before and after the use of antibiotics and lessen the variability of accuracy measures of the classifier. To ev…

Classification algorithms; feature selection; high dimensionality; machine learningInformation Technology and Management Science
researchProduct

Using differential LARS algorithm to study the expression profile of a sample of patients with latex-fruit syndrome

2010

Natural rubber latex IgE-mediated hypersensitivity is one of the most important health problems in allergy during recent years. The prevalence of individuals allergic to latex shows an associated hypersensitivity to some plant-derived foods, especially freshly consumed fruit. This association of latex allergy and allergy to plant-derived foods is called latex-fruit syndrome. The aim of this study is to use the differential geometric generalization of the LARS algorithm to identify candidate genes that may be associated with the pathogenesis of allergy to latex or vegetable food.

Latex-fruit syndrome variable selection penalized regression high dimensionality LARS.Settore SECS-S/01 - Statistica
researchProduct

Using differential geometric LARS algorithm to study the expression profile of a sample of patients with latex-fruit syndrome

2011

Natural rubber latex IgE-mediated hypersensitivity is one of the most important health problems in allergy during recent years. The prevalence of individuals allergic to latex shows an associated hypersensitivity to some plant-derived foods, especially freshly consumed fruit. This association of latex allergy and allergy to plant-derived foods is called latex-fruit syndrome. The aim of this study is to use the differential geometric generalization of the LARS algorithm to identify candidate genes that may be associated with the pathogenesis of allergy to latex or vegetable.

Settore SECS-S/01 - StatisticaLatex-fruit syndrome variable selection penalized regression high dimensional LARS
researchProduct