Search results for "Hierarchical Clustering"

showing 10 items of 56 documents

Hierarchically nested factor model from multivariate data

2005

We show how to achieve a statistical description of the hierarchical structure of a multivariate data set. Specifically we show that the similarity matrix resulting from a hierarchical clustering procedure is the correlation matrix of a factor model, the hierarchically nested factor model. In this model, factors are mutually independent and hierarchically organized. Finally, we use a bootstrap based procedure to reduce the number of factors in the model with the aim of retaining only those factors significantly robust with respect to the statistical uncertainty due to the finite length of data records.

Data recordsStructure (mathematical logic)Multivariate statisticsCovariance matrixFinance commerce hierarchical structureGeneral Physics and AstronomySimilarity matrixFOS: Physical sciencesDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural Networkscomputer.software_genreHierarchical clusteringCondensed Matter - Other Condensed MatterSet (abstract data type)Factor (programming language)Data miningcomputerMathematicscomputer.programming_languageOther Condensed Matter (cond-mat.other)
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Mismatches between objective parameters and measured perception assessment in room acoustics: a holistic approach

2014

Psychoacoustic research in the field of concert halls has revealed that many aspects concerning listening perception have yet to be totally understood. On the one hand, the objective room acoustics of performance spaces are reflected in parameters, some standardized and some not, but these are related to a limited number of perceptual attributes of human response. In general, these objective parameters cannot accurately describe the acoustic details due to their inherent simplification. Under these premises, impulse responses (576 receivers) are measured in 16 concert halls, according to standard procedures, and the perception and satisfaction of the occupants of the rooms are evaluated by …

EngineeringEnvironmental EngineeringSpeech recognitionmedia_common.quotation_subjectGeography Planning and DevelopmentPerceptive acoustic evaluationAcoustic qualityMachine learningcomputer.software_genreConcert-goers responsesField (computer science)CorrelationPerceptionActive listeningPsychoacousticsMultidimensional scalingConcert hallCivil and Structural Engineeringmedia_commonbusiness.industryBuilding and ConstructionRoom acousticsHierarchical clusteringFISICA APLICADAArtificial intelligencebusinessMATEMATICA APLICADAcomputerRoom acousticsMultidimensional scaling
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GIS-data related route optimization, hierarchical clustering, location optimization, and kernel density methods are useful for promoting distributed …

2019

Currently, geographic information system (GIS) models are popular for studying location-allocation-related questions concerning bioenergy plants. The aim of this study was to develop a model to investigate optimal locations for two different types of bioenergy plants, for farm and centralized biogas plants, and for wood terminals in rural areas based on minimizing transportation distances. The optimal locations of biogas plants were determined using location optimization tools in R software, and the optimal locations of wood terminals were determined using kernel density tools in ArcGIS. The present case study showed that the utilized GIS tools are useful for bioenergy-related decision-maki…

Geographic information systemPower stationbiomassapaikkatiedot020209 energy116 Chemical sciencesKernel density estimationta220tuotantoketjutEnergy Engineering and Power Technologywood terminal02 engineering and technologyAgricultural engineeringterminaalitverkostoanalyysioptimointi020401 chemical engineeringBiogasBioenergybiogas0202 electrical engineering electronic engineering information engineeringbiomassa (teollisuus)0204 chemical engineeringnetwork analysista218ta113tehtaatbiokaasuRenewable Energy Sustainability and the Environmentbusiness.industrycircular economypuut (kasvit)SizingHierarchical clusteringbioenergiapaikkatietojärjestelmätkiertotalousEnvironmental sciencelocation-allocationbiokaasulaitoksetRural areabusinessSustainable Energy Technologies and Assessments
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Basic Chemometric Tools

2013

Abstract The authentication of protected designation of origin and other protected geographical indications for foods involves the need for a deep knowledge of these kinds of samples and the correct identification of appropriate markers that are suitable to be used for authentication purposes. For this, significance tests must be developed and applied to provide evidence in a fast and accurate way; from this, it seems clear that advances in analytical tools, to obtain data regarding food chemical composition, and chemometric data treatments must be continued to provide to the users powerful identification methodologies. In this sense, the objective must be to differentiate between foods pro…

Identification (information)business.industryComputer sciencePrincipal component analysisDeep knowledgeArtificial intelligencebusinessMachine learningcomputer.software_genrecomputerAuthentication (law)Hierarchical clustering
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Knowledge Discovery from the Programme for International Student Assessment

2017

The Programme for International Student Assessment (PISA) is a worldwide study that assesses the proficiencies of 15-year-old students in reading, mathematics, and science every three years. Despite the high quality and open availability of the PISA data sets, which call for big data learning analytics, academic research using this rich and carefully collected data is surprisingly sparse. Our research contributes to reducing this deficit by discovering novel knowledge from the PISA through the development and use of appropriate methods. Since Finland has been the country of most international interest in the PISA assessment, a relevant review of the Finnish educational system is provided. T…

Knowledge managementmedia_common.quotation_subjectknowledge discoveryBig dataLearning analytics02 engineering and technologyKnowledge extractionbig data020204 information systemsReading (process)Political science0202 electrical engineering electronic engineering information engineeringMathematics educationQuality (business)Cluster analysismedia_commonStatistical hypothesis testinglearning analyticsbusiness.industry05 social sciencesPISA050301 educationTest (assessment)businesshierarchical clustering0503 education
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Reproducibility of CT Radiomic Features within the Same Patient: Influence of Radiation Dose and CT Reconstruction Settings.

2019

Background Results of recent phantom studies show that variation in CT acquisition parameters and reconstruction techniques may make radiomic features largely nonreproduceable and of limited use for prognostic clinical studies. Purpose To investigate the effect of CT radiation dose and reconstruction settings on the reproducibility of radiomic features, as well as to identify correction factors for mitigating these sources of variability. Materials and Methods This was a secondary analysis of a prospective study of metastatic liver lesions in patients who underwent staging with single-energy dual-source contrast material-enhanced staging CT between September 2011 and April 2012. Technique p…

MaleContrast MediaRadiation Dosage030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineMedicineHumansRadiology Nuclear Medicine and imagingProspective StudiesCluster analysisNeoplasm StagingReproducibilitybusiness.industryRadiation doseLiver NeoplasmsReproducibility of ResultsReconstruction algorithmMiddle AgedHierarchical clusteringFeature (computer vision)radiomics030220 oncology & carcinogenesisRadiographic Image Interpretation Computer-AssistedFemaleTomographybusinessNuclear medicineTomography X-Ray ComputedCt reconstructionAlgorithmsRadiology
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Non-Hierarchical Clustering as a method to analyse an open-ended questionnaire on algebraic thinking

2016

The problem of taking a data set and separating it into subgroups, where the members of each subgroup are more similar to each other than they are to members outside the subgroup, has been extensively studied in science and mathematics education research. Student responses to written questions and multiple-choice tests have been characterised and studied using several qualitative and/or quantitative analysis methods. However, there are inherent difficulties in the categorisation of student responses in the case of open-ended questionnaires. Very often, researcher bias means that the categories picked out tend to find the groups of students that the researcher is seeking out. In this paper, …

Multivariate analysisMathematical problemAlgebraic thinkinglcsh:Education (General)Education0502 economics and businessMathematics educationalgebraic thinking; cluster analysis; mathematics education; quantitative analysisCluster analysiAlgebraic numberQuantitative analysisCluster analysisMathematical logiclcsh:LC8-6691lcsh:Special aspects of educationquantitative analysis05 social sciences050301 educationalgebraic thinkingmathematics educationMathematics educationHierarchical clusteringQuantitative analysis (finance)Education Clustering Algebraiclcsh:L7-991Psychology0503 education050203 business & managementcluster analysisAlgebraic thinkingSouth African Journal of Education
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A quantitative analysis of Educational Data through the Comparison between Hierarchical and Not-Hierarchical Clustering

2017

Many research papers have studied the problem of taking a set of data and separating it into subgroups through the methods of Cluster Analysis. However, the variables and parameters involved in Cluster Analysis have not always been outlined and criticized, especially in the field of Science Education. Moreover, in the field of Science Education, a comparison between two different Clustering methods is not discussed in the literature. Conceptions of students about modeling in physic are investigated by using an open-ended questionnaire. The questionnaire is analyzed through Clustering methods. The clustering results obtained by using the two methods are compared and show a good coherence bet…

Not-hierarchical cluster analysi3304Settore FIS/08 - Didattica E Storia Della Fisicacomputer.software_genre01 natural sciencesScience educationEducationSet (abstract data type)010104 statistics & probability0101 mathematicsCluster analysisEvaluationScience educationHierarchical cluster analysiPoint (typography)Applied Mathematics05 social sciencesModeling050301 educationCoherence (statistics)Settore MAT/04 - Matematiche Complementarivaluation hierarchical cluster analysis modeling not-hierarchical cluster analysis science educationField (geography)Hierarchical clusteringQuantitative analysis (finance)Data mining0503 educationcomputer
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Correlation, hierarchies, and networks in financial markets

2010

We discuss some methods to quantitatively investigate the properties of correlation matrices. Correlation matrices play an important role in portfolio optimization and in several other quantitative descriptions of asset price dynamics in financial markets. Specifically, we discuss how to define and obtain hierarchical trees, correlation based trees and networks from a correlation matrix. The hierarchical clustering and other procedures performed on the correlation matrix to detect statistically reliable aspects of the correlation matrix are seen as filtering procedures of the correlation matrix. We also discuss a method to associate a hierarchically nested factor model to a hierarchical tre…

Organizational Behavior and Human Resource ManagementEconomics and EconometricsPhysics - Physics and SocietyCorrelation based networkKullback–Leibler divergenceStability (learning theory)FOS: Physical sciencesKullback–Leibler distancePhysics and Society (physics.soc-ph)computer.software_genreHierarchical clusteringFOS: Economics and businessCorrelationMultivariate analysis Hierarchical clustering Correlation based networks Bootstrap validation Factor models Kullback–Leibler distancePortfolio Management (q-fin.PM)Bootstrap validationQuantitative Finance - Portfolio ManagementMathematicsFactor analysisStatistical Finance (q-fin.ST)Covariance matrixMultivariate analysiQuantitative Finance - Statistical FinanceHierarchical clusteringFactor modelTree (data structure)Physics - Data Analysis Statistics and ProbabilityData miningPortfolio optimizationcomputerData Analysis Statistics and Probability (physics.data-an)
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Euphosantianane E–G: Three New Premyrsinane Type Diterpenoids from Euphorbia sanctae-catharinae with Contribution to Chemotaxonomy

2019

Euphorbia species were widely used in traditional medicines for the treatment of several diseases. From the aerial parts of Egyptian endemic plant, Euphorbia sanctae-catharinae, three new premyrsinane diterpenoids, namely, euphosantianane E&ndash

Pharmaceutical ScienceAgglomerative hierarchical clustering01 natural sciencesArticlepremyrsinane diterpenoidsAnalytical Chemistrylcsh:QD241-441TerpeneType (biology)lcsh:Organic chemistryEuphorbiaDrug DiscoveryPhysical and Theoretical ChemistryEuphorbiaMolecular StructurebiologyTraditional medicinePlant Extracts010405 organic chemistryOrganic ChemistryeuphorbiaceaeEuphorbiaceaeEuphorbia sanctae-catharinaePlant Components Aerialendemic plantchemotaxonomic significancebiology.organism_classificationAntineoplastic Agents Phytogenic0104 chemical sciences010404 medicinal & biomolecular chemistryChemistry (miscellaneous)Chemotaxonomyeuphosantianane E–G<i>Euphorbia sanctae-catharinae</i>Molecular MedicineEgyptDiterpenesDrug Screening Assays AntitumorMolecules
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