Search results for " Hierarchical clustering"

showing 4 items of 4 documents

Multivariate statistical analysis of a large odorants database aimed at revealing similarities and links between odorants and odors

2017

International audience; The perception of odor is an important component of smell; the first step of odor detection, and the discrimination of structurally diverse odorants depends on their interactions with olfactory receptors (ORs). Indeed, the perception of an odor's quality results from a combinatorial coding, in which the deciphering remains a major challenge. Several studies have successfully established links between odors and odorants by categorizing and classifying data. Hence, the categorization of odors appears to be a promising way to manage odors. In the proposed study, we performed a computational analysis using odor descriptions of the odorants present in Flavor-Base 9th Edit…

0301 basic medicinemultidimensional scalingmedia_common.quotation_subjectAgglomerative hierarchical clusteringKohonen self-organizing mapsodorants03 medical and health sciences0302 clinical medicinePerceptionComputational analysisMultidimensional scalingmedia_commonChemistrybusiness.industrymusculoskeletal neural and ocular physiologyPattern recognitionKohonen self organizing mapGeneral Chemistrycategorization030104 developmental biologyCategorizationOdorodor notesagglomerative hierarchical clusteringArtificial intelligenceMultivariate statisticalbusiness[SDV.AEN]Life Sciences [q-bio]/Food and Nutrition030217 neurology & neurosurgerypsychological phenomena and processesFood Science
researchProduct

A New Approach to Investigate Students’ Behavior by Using Cluster Analysis as an Unsupervised Methodology in the Field of Education

2016

The problem of taking a set of data and separating it into subgroups where the ele- ments of each subgroup are more similar to each other than they are to elements not in the subgroup has been extensively studied through the statistical method of cluster analysis. In this paper we want to discuss the application of this method to the field of education: particularly, we want to present the use of cluster analysis to separate students into groups that can be recognized and characterized by common traits in their answers to a questionnaire, without any prior knowledge of what form those groups would take (unsupervised classification). We start from a detailed study of the data processing need…

Data processingPoint (typography)business.industrySettore FIS/08 - Didattica E Storia Della Fisica020208 electrical & electronic engineering05 social sciences050301 educationSample (statistics)02 engineering and technologyGeneral Medicinecomputer.software_genreDisease clusterField (computer science)Hierarchical clusteringSet (abstract data type)Quantitative analysis (finance)Education Unsupervised Methods Hierarchical Clustering Not-Hierarchical Clustering Quantitative Analysis0202 electrical engineering electronic engineering information engineeringArtificial intelligenceData miningbusiness0503 educationcomputerNatural language processingMathematics
researchProduct

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)
researchProduct

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
researchProduct