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146 results for “High Dimension”

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Research ArticleOpen accessPhrase in the titleCOMBINATION OF DIFFERENCE SUBSPACE AND OPPURTUNISTIC CLUSTERING ON HIGH DIMENSIONAL DATAM. Ravichandran, A. ShanmugamClustering is recognized as sigificant technique for analysing data and concentric effort has been taken in different domains comprises of recognition of pattern, statistical analysis and data mining for decades. Subspace clustering is developed from the group of cluster objects from all subspaces of a dataset. During clustering of objects involing higher dimension, the accuracy and effectiveness of traditional clustering … …Journal of Computer Science, Vol. 10, Issue 8 · 11 Mar 2014 · 6,355 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleFeature Selection for High Dimensional Data: An Evolutionary Filter ApproachAnwar Ali Yahya, Addin Osman, Abd Rahman Ramli, Adlan BalolaProblem statement: Feature selection is a task of crucial importance for the application of machine learning in various domains. In addition, the recent increase of data dimensionality poses a severe challenge to many existing feature selection approaches with respect to efficiency and effectiveness. As an example, genetic algorithm is an effective search algorithm that lends itself directly to feature selection; … …Journal of Computer Science, Vol. 7, Issue 5 · 9 May 2011 · 7,946 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleInversion of Covariance Matrix for High Dimension DataSamruam ChongcharoenProblem statement: In the testing statistic problem for the mean vector of independent and identically distributed multivariate normal random vectors with unknown covariance matrix when the data has sample size less than the dimension n≤p, for example, the data came from DNA microarrays where a large number of gene expression levels are measured on relatively few subjects, the p×p sample … …Journal of Mathematics and Statistics, Vol. 7, Issue 3 · 27 Jul 2011 · 7,869 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleOne-Sided Multivariate Tests for High Dimensional DataSamruam ChongcharoenProblem statement: For a multivariate normal population with size smaller than dimension, n<p, the likelihood ratio tests of the null hypothesis that the mean vector was zero with a one-sided alternative were no longer valid because they involved with sample covariance matrix which was singular. Approach: The test statistics for one-sided multivariate hypotheses with n<p were proposed. Results: The simulation … …Journal of Mathematics and Statistics, Vol. 8, Issue 2 · 20 Jun 2012 · 7,261 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleThe Analysis of High Dimensional Contingency Table with InteractionsKeorapetse Sediakgotla, Lesego Gabaitiri, Keamogetse Setlhare et al.This paper is focused on the analysis of categorical data in a 2 × c × K contingency table. The theoretical frame work of a 2 × c design is extended to 2 × c × K with provision for testing interactions among subsets of either lower or upper columns of the designated table. The developed chi square tests for … …American Journal of Applied Sciences, Vol. 14, Issue 8 · 30 Aug 2017 · 7,651 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Test on the Multivariate Behrens–Fisher Problem in High–Dimensional Data by Block Covariance EstimationParanut Sukcharoen, Samruam ChongcharoenIn this paper, we proposed a new testing statistic for testing the equality of mean vectors from two multivariate normal populations when the covariance matrices are unknown and unequal in high–dimensional data. A new test is proposed based on the idea of keeping more information from the sample covariance matrices as much as possible. A proposed test is invariant under … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 2 Apr 2019 · 7,369 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Test for Two-Sample Repeated Measures Designs: Effect of High-Dimensional DataBoonyarit Choopradit, Samruam ChongcharoenProblem statement: High-dimensional repeated measures data are increasingly encountered in various areas of modern science since classical multivariate statistics, e.g,. Hotelling’s T2, are not well defined in the case of high-dimensional data. Approach: In this study, the test statistics with no specific form of covariance matrix for analyzing high-dimensional two-sample repeated measures designs with common equal covariance are proposed. The … …Journal of Mathematics and Statistics, Vol. 7, Issue 4 · 28 Oct 2011 · 7,328 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Class of Region-preserving Space Transformations for Indexing High-dimensional DataRatko Orlandic, Jack LukaszukThis study introduces a class of region preserving space transformation (RPST) schemes for accessing high-dimensional data. The access methods in this class differ with respect to their space-partitioning strategies. The study develops two new static partitioning schemes that can split each dimension of the space within linear space complexity. They also support an effective mechanism for handling skewed data in … …Journal of Computer Science, Vol. 1, Issue 1 · 31 Mar 2005 · 6,919 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleShots Temporal Prediction Rules for High-Dimensional Data of Semantic Video RetrievalShaimaa Toriah Mohamed Toriah, Atef Zaki Ghalwash, Aliaa A.A. YoussifTemporal consistency stands as a vital property in semantic video retrieval. Few research studies can exploit this useful property. Most of the used methods in those studies depend on rules defined by experts and use ground-truth annotation. The Ground-truth annotation is time-consuming, labor intensive and domain specific. Additionally, it involves a limited number of annotated concepts and a limited number … …American Journal of Applied Sciences, Vol. 15, Issue 1 · 30 Jan 2018 · 8,117 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSimulations of Two-dimensional High Speed Turbulent Compressible Flow in a Diffuser and a Nozzle Blade CascadeK. C. Ng, M. Z. Yusoff, T. F. YusafThis research describes the development of a new structured 2D CFD solver for compressible flow. The high-speed turbulent flow in a diffuser and a cascade of nozzle blade is predicted using standard k-ε turbulence model. The new finite volume CFD solver employs second-order accurate central differencing scheme for spatial discretization and multi-stage Runge-Kutta time integration to solve the set of … …American Journal of Applied Sciences, Vol. 2, Issue 9 · 30 Sep 2005 · 6,550 accessesView PDFCite