Search results for " dimensionality"

showing 10 items of 129 documents

Nonlinear data description with Principal Polynomial Analysis

2012

Principal Component Analysis (PCA) has been widely used for manifold description and dimensionality reduction. Performance of PCA is however hampered when data exhibits nonlinear feature relations. In this work, we propose a new framework for manifold learning based on the use of a sequence of Principal Polynomials that capture the eventually nonlinear nature of the data. The proposed Principal Polynomial Analysis (PPA) is shown to generalize PCA. Unlike recently proposed nonlinear methods (e.g. spectral/kernel methods and projection pursuit techniques, neural networks), PPA features are easily interpretable and the method leads to a fully invertible transform, which is a desirable property…

business.industryCodingDimensionality reductionNonlinear dimensionality reductionDiffusion mapSparse PCAComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONElastic mapPattern recognitionManifold LearningClassificationKernel principal component analysisComputingMethodologies_PATTERNRECOGNITIONPrincipal component analysisPrincipal Polynomial AnalysisArtificial intelligencePrincipal geodesic analysisbusinessDimensionality ReductionMathematics
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Local dimensionality reduction within natural clusters for medical data analysis

2005

Inductive learning systems have been successfully applied in a number of medical domains. Nevertheless, the effective use of these systems requires data preprocessing before applying a learning algorithm. Especially it is important for multidimensional heterogeneous data, presented by a large number of features of different types. Dimensionality reduction is one commonly applied approach. The goal of this paper is to study the impact of natural clustering on dimensionality reduction for classification. We compare several data mining strategies that apply dimensionality reduction by means of feature extraction or feature selection for subsequent classification. We show experimentally on micr…

business.industryComputer scienceFeature vectorDimensionality reductionFeature extractionPattern recognitionFeature selectioncomputer.software_genreArtificial intelligenceData pre-processingData miningMultidimensional systemsbusinessCluster analysiscomputerCurse of dimensionality
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A novel method for network intrusion detection based on nonlinear SNE and SVM

2017

In the case of network intrusion detection data, pre-processing techniques have been extensively used to enhance the accuracy of the model. An ideal intrusion detection system (IDS) is one that has appreciable detection capability overall the group of attacks. An open research problem of this area is the lower detection rate for less frequent attacks, which result from the curse of dimensionality and imbalanced class distribution of the benchmark datasets. This work attempts to minimise the effects of imbalanced class distribution by applying random under-sampling of the majority classes and SMOTE-based oversampling of minority classes. In order to alleviate the issue arising from the curse…

business.industryComputer science[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingDimensionality reductionFeature vectorPattern recognitionGeneral MedicineIntrusion detection systemSupport vector machineBenchmark (computing)EmbeddingRadial basis functionArtificial intelligencebusinessCurse of dimensionality
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Semisupervised kernel orthonormalized partial least squares

2012

This paper presents a semisupervised kernel orthonormalized partial least squares (SS-KOPLS) algorithm for non-linear feature extraction. The proposed method finds projections that minimize the least squares regression error in Hilbert spaces and incorporates the wealth of unlabeled information to deal with small size labeled datasets. The method relies on combining a standard RBF kernel using labeled information, and a generative kernel learned by clustering all available data. The positive definiteness of the kernels is proven, and the structure and information content of the derived kernels is studied. The effectiveness of the proposed method is successfully illustrated in standard UCI d…

business.industryFeature extractionNonlinear dimensionality reductionPattern recognitionComputingMethodologies_PATTERNRECOGNITIONKernel methodVariable kernel density estimationKernel (statistics)Radial basis function kernelPartial least squares regressionArtificial intelligenceCluster analysisbusinessMathematics2012 IEEE International Workshop on Machine Learning for Signal Processing
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Solvatochromy and electro-optical study of new fluorine-containing chromophores

1998

technology requires tailored functional materials which fulfill the demands for optimal operation parameters, reliability andprocessability. Organic chromophores and polymers which contain covalently bound chromophores are promising materialclasses which can satisfy a broad spectrum of demands on functional materials for photonics, and they are, therefore,favorites for the development of new photonic devices. However, it is almost impossible to satisfy all physico-chemical andtechnological requirements simultaneously with a polymer consisting of only one type of functional unit. The developmentof a series of different building blocks which allow to cover the whole range of physico-chemical …

chemistry.chemical_classificationMaterials sciencebusiness.industryInstitut für Physik und AstronomieNonlinear opticsPolymerElectro-opticsPlanarity testingNonlinear systemchemistryOptoelectronicsPhotonicsFunctional polymersbusinessCurse of dimensionalitySPIE Proceedings
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1,4-Bis(arylthio)but-2-enes as Assembling Ligands for (Cu2X2)n (X = I, Br; n = 1, 2) Coordination Polymers: Aryl Substitution, Olefin Configuration, …

2016

CuI reacts with E-PhS(CH2CH═CHCH2)SPh, L1, to afford the coordination polymer (CP) [Cu2I2{μ-E-PhS(CH2CH═CHCH2)SPh}2]n (1a). The unprecedented square-grid network of 1 is built upon alternating two-dimensional (2D) layers with an ABAB sequence and contains rhomboid Cu2(μ2-I)2 clusters as secondary building units (SBUs). Notably, layer A, interconnected by bridging L1 ligands, contains exclusively dinuclear units with short Cu···Cu separations [2.6485(7) A; 115 K]. In contrast, layer B exhibits Cu···Cu distances of 2.8133(8) A. The same network is observed when CuBr reacts with L1. In the 2D network of [Cu2Br2{μ-E-PhS(CH2CH═CHCH2)SPh}2]n (1b), isotype to 1a, one square-grid-type layer contain…

chemistry.chemical_classificationOlefin fiber010405 organic chemistryCoordination polymerStereochemistryArylHalideGeneral ChemistryPolymer010402 general chemistryCondensed Matter Physics01 natural sciences0104 chemical scienceschemistry.chemical_compoundCrystallographychemistryGeneral Materials ScienceSBusLuminescenceCurse of dimensionalityCrystal Growth & Design
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The Three Steps of Clustering in the Post-Genomic Era: A Synopsis

2011

Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from Statistics to Computer Science. Following Handl et al., it can be summarized as a three step process: (a) choice of a distance function; (b) choice of a clustering algorithm; (c) choice of a validation method. Although such a purist approach to clustering is hardly seen in many areas of science, genomic data require that level of attention, if inferences made from cluster analysis have to be of some relevance to biomedical research. Unfortunately, the high dimensionality of the data and their noisy nature makes cluster analysis of genomic data particul…

cluster validation indicesSettore INF/01 - InformaticaProcess (engineering)Computer sciencebusiness.industryGenomic datadistance functionMachine learningcomputer.software_genreObject (computer science)ClusteringCluster algorithmPredictive powerRelevance (information retrieval)Artificial intelligenceHigh dimensionalitybusinessCluster analysiscomputer
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Factorial Structure and Psychometric Properties of the Sensation Seeking Scale – Form V (SSS-V) in a Sample of Italian Adolescents

2013

The present study was designed to evaluate the psychometric properties of the Sensation Seeking Scale – Form V (SSS-V) for the Italian-speaking population. The instrument was administered to 1,530 high school and college students. A second group of 268 high school students completed the SSS-V and the Impulsiveness Questionnaire (IVE). Exploratory factor analysis highlighted a 2-factor structure, Thrill and Adventure Seeking (TAS) and Disinhibition (Dis). Confirmatory factor analysis revealed an adequate model fit. Internal consistency of the subscales was marginally supported using the alpha reliability measure. Convergent validity was supported by significant positive correlations between …

education.field_of_studylcsh:BF1-990PopulationSettore M-PSI/03 - PsicometriaDiscriminant validitySample (statistics)psychometric propertiesdimensionalitysensation seeking SSS-V factor structure psychometric properties dimensionality adolescence personality measurementsensation seekingfactor structureConfirmatory factor analysisExploratory factor analysisTest (assessment)Developmental psychologylcsh:PsychologyConvergent validitypersonality measurementSSS-VSensation seekingadolescenceeducationPsychologyGeneral PsychologyEurope’s Journal of Psychology
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The Importance of Electronic Dimensionality in Multiorbital Radical Conductors

2019

The exceptional performance of oxobenzene-bridged bis-1,2,3-dithiazolyls 6 as single-component neutral radical conductors arises from the presence of a low-lying π-lowest unoccupied molecular orbital, which reduces the potential barrier to charge transport and increases the kinetic stabilization energy of the metallic state. As part of ongoing efforts to modify the solid-state structures and transport properties of these so-called multiorbital materials, we report the preparation and characterization of the acetoxy, methoxy, and thiomethyl derivatives 6 (R = OAc, OMe, SMe). The crystal structures are based on ribbonlike arrays of radicals laced together by S···N′ and S···O′ secondary bondin…

electronic dimensionalitymultiorbital radical conductorsvapaat radikaalitkiteetsähkönjohtavuus
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Communication between iron(II) building blocks in cooperative spin transition phenomena

2003

[EN] In the present article we discuss the cooperative nature of the spin crossover phenomenon in iron(II) complexes, providing a perspective of the state of the art in this area. The first aspect we discuss is the role of the intermolecular interactions, more precisely the ¿-interactions, in mononuclear complexes. We show that by playing with the nature of the ligands, aliphatic, aromatic, or extended aromatic, it is possible to create stronger cohesive forces and receive a more cooperative response from the compound. In the next step the singular family of bipyrimidine-bridged iron(II) dinuclear compounds is presented as the simplest example of polynuclear spin crossover complexes exhibit…

genetic structuresStereochemistryChemistryIntermolecular forceSupramolecular chemistrySpin transitionSpin transitionIron(II) complexesInorganic ChemistryChemical physicsSpin crossoverFISICA APLICADAIntramolecular forceMaterials ChemistryMolecular magnetismPhysical and Theoretical ChemistrySupramolecular chemistryTopology (chemistry)Curse of dimensionalityCoordination Chemistry Reviews
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