Data dimensionality estimation methods: A survey.

From MaRDI portal
Publication:1425989

DOI10.1016/S0031-3203(03)00176-6zbMath1059.68100MaRDI QIDQ1425989

Francesco Camastra

Publication date: 14 March 2004

Published in: Pattern Recognition (Search for Journal in Brave)




Related Items (27)

Classification using the Zipfian kernelIAN: Iterated Adaptive Neighborhoods for Manifold Learning and Dimensionality EstimationIntrinsic dimension estimation based on local adjacency informationDANCo: an intrinsic dimensionality estimator exploiting angle and norm concentrationAnderson relaxation test for intrinsic dimension selection in model-based clusteringNonlinear shape-manifold learning approach: concepts, tools and applicationsOptimization of the maximum likelihood estimator for determining the intrinsic dimensionality of high-dimensional dataIntrinsic dimension estimation: relevant techniques and a benchmark frameworkMulti-view kernel consensus for data analysisSymmetric positive definite manifold learning and its application in fault diagnosisGeneral stochastic separation theorems with optimal boundsEstimating dynamical dimensions from noisy observationsNovel high intrinsic dimensionality estimatorsDirectional entropy based model for diffusivity-driven tumor growthDistance-based index structures for fast similarity searchPivot selection: dimension reduction for distance-based indexingGaussian bandwidth selection for manifold learning and classificationA manifold learning approach to dimensionality reduction for modeling dataDimension estimation using weighted correlation dimension methodFeature selection based on composition of rough sets induced by feature granulationMultiscale topology optimization using neural network surrogate modelsIntrinsic dimension estimation: advances and open problemsMulti-class pairwise linear dimensionality reduction using heteroscedastic schemesLearning algebraic varieties from samplesIntrinsic dimension estimation of manifolds by incising ballsGeodesic distances in the intrinsic dimensionality estimation using packing numbersAn algorithm for reducing the dimension and size of a sample for data exploration procedures


Uses Software


Cites Work


This page was built for publication: Data dimensionality estimation methods: A survey.