Search results for "Multiple data"

showing 5 items of 5 documents

<title>Dynamic integration of multiple data mining techniques in a knowledge discovery management system</title>

1999

One of the most important directions in improvement of data mining and knowledge discovery, is the integration of multiple classification techniques of an ensemble of classifiers. An integration technique should be able to estimate and select the most appropriate component classifiers from the ensemble. We present two variations of an advanced dynamic integration technique with two distance metrics. The technique is one variation of the stacked generalization method, with an assumption that each of the component classifiers is the best one, inside a certain sub area of the entire domain area. Our technique includes two phases: the learning phase and the application phase. During the learnin…

Computer sciencebusiness.industryWeighted votingcomputer.software_genreMachine learningExpert systemMultiple dataMatrix (mathematics)Information extractionComputingMethodologies_PATTERNRECOGNITIONKnowledge extractionManagement systemData miningArtificial intelligencebusinesscomputerClassifier (UML)Data Mining and Knowledge Discovery: Theory, Tools, and Technology
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Analysis of multi-source metabolomic data using joint and individual variation explained (JIVE).

2015

Metabolic profiling is increasingly being used for understanding biological processes but there is no single analytical technique that provides a complete quantitative or qualitative profiling of the metabolome. Data fusion (i.e. joint analysis of data from multiple sources) has the potential to circumvent this issue facilitating knowledge discovery and reliable biomarker identification. Another field of application of data fusion is the simultaneous analysis of metabolomic changes through several biofluids or tissues. However, metabolomics typically deals with large datasets, with hundreds to thousands of variables and the identification of shared and individual factors or structures acros…

Data sourceComputer scienceAnalytical techniqueStatistics as TopicAnalytical chemistryUrinalysisSensor fusioncomputer.software_genreBiochemistryAnalytical ChemistryMultiple dataMetabolomicsKnowledge extractionElectrochemistryEnvironmental ChemistryProfiling (information science)HumansMetabolomicsData miningcomputerSpectroscopyMulti-sourceBlood Chemical AnalysisSoftwareThe Analyst
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Patrimonio industrial rural de Teruel: un ejemplo de abandono del territorio

2018

espanolEl objetivo de este articulo es analizar la naturaleza, distribucion, importancia y el estado del patrimonio industrial disperso de la provincia de Teruel que cumpla los siguientes criterios: estar fuera de nucleos de poblacion, estar abandonado, no estar completamente asolado y otros. Se han explorado multiples fuentes: cartografia historica; publicaciones, bases de datos (archivos, SIPCA, etc.); contactos mediante redes sociales y varias entrevistas. Con la informacion obtenida se ha realizado un analisis mediante SIG. En conclusion, el numero de industrias abandonadas o destruidas es ingente en numeros absolutos y en comparacion con lo restaurado. El trabajo amplia y actualiza par…

Multiple dataGeographyIndustrial heritagePatrimoni culturalHumanitiesGeographicalia
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UNCLES: Method for the identification of genes differentially consistently co-expressed in a specific subset of datasets

2015

Background Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently repres…

Multiple datasets analysisMethodology ArticleGene Expression ProfilingCell CycleGenes FungalBi-CoPaMSaccharomyces cerevisiaeConsistent co-expressionBiochemistryComputer Science ApplicationsComputingMethodologies_PATTERNRECOGNITIONGenome-wide analysisUNCLESCluster AnalysisGenome FungalMolecular BiologyOligonucleotide Array Sequence Analysis
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Multiple factor analysis: principal component analysis for multitable and multiblock data sets

2013

Multiple factor analysis MFA, also called multiple factorial analysis is an extension of principal component analysis PCA tailored to handle multiple data tables that measure sets of variables coll...

Statistics and ProbabilityMeasure (data warehouse)business.industryPattern recognitionMultiple dataMultiple correspondence analysisRelationship squareMultiple factor analysisPrincipal component analysisArtificial intelligenceFactorial analysisGeneralized singular value decompositionbusinessMathematicsWiley Interdisciplinary Reviews: Computational Statistics
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