Search Results - Functional data analysis Curve alignment Curve clustering k-mean algorithm

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  1. 1

    Probabilistic K-means with Local Alignment for Clustering and Motif Discovery in Functional Data by Cremona, Marzia A., Chiaromonte, Francesca

    ISSN: 1061-8600, 1537-2715
    Published: Alexandria Taylor & Francis 03.07.2023
    “… In order to identify these shared curve portions, our method leverages ideas from functional data analysis…”
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    Journal Article
  2. 2

    Probabilistic \(K\)-mean with local alignment for clustering and motif discovery in functional data by Cremona, Marzia A, Chiaromonte, Francesca

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 07.07.2020
    Published in arXiv.org (07.07.2020)
    “… In order to identify these shared curve portions, our method leverages ideas from functional data analysis…”
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    Paper
  3. 3

    Visualizing, clustering, and characterizing activity-trip sequences via weighted sequence alignment and functional data analysis by Song, Ying, Ren, Siyang, Wolfson, Julian, Zhang, Yaxuan, Brown, Roland, Fan, Yingling

    ISSN: 0968-090X, 1879-2359
    Published: Elsevier Ltd 01.05.2021
    “…•Conduct sensitivity analysis of sample interval and weighting schemas.•Summarize and compare activity-travel patterns through functional data analysis…”
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    Journal Article
  4. 4

    K-means clustering of item characteristic curves and item information curves via functional principal component analysis by Fortuna, Francesca, Maturo, Fabrizio

    ISSN: 0033-5177, 1573-7845
    Published: Dordrecht Springer Netherlands 15.09.2019
    Published in Quality & quantity (15.09.2019)
    “… Nevertheless, tests assessment through IRT models and the related clustering algorithms generally focus on the analysis of item parameters…”
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    Journal Article
  5. 5

    Functional Data Analysis in Sport Science: Example of Swimmers’ Progression Curves Clustering by Leroy, Arthur, MARC, Andy, DUPAS, Olivier, REY, Jean Lionel, Gey, Servane

    ISSN: 2076-3417, 2076-3417
    Published: Basel MDPI AG 01.10.2018
    Published in Applied sciences (01.10.2018)
    “…) or functional clustering algorithms are presented and compared on simulated data. Finally, the problem of the detection of promising young swimmers is addressed through a curve clustering procedure on a real data set of performance progression curves…”
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    Journal Article
  6. 6
  7. 7

    An introduction to functional data analysis and a principal component approach for testing the equality of mean curves by Horváth, Lajos, Rice, Gregory

    ISSN: 1139-1138, 1988-2807
    Published: Milan Springer Milan 01.09.2015
    Published in Revista matemática complutense (01.09.2015)
    “…We give an introduction to functional data analysis, with examples, and provide a brief review of the literature…”
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    Journal Article
  8. 8

    k -mean alignment for curve clustering by Sangalli, Laura M., Secchi, Piercesare, Vantini, Simone, Vitelli, Valeria

    ISSN: 0167-9473, 1872-7352
    Published: Amsterdam Elsevier B.V 01.05.2010
    Published in Computational statistics & data analysis (01.05.2010)
    “… clustering nor by simple curve alignment. The procedure is illustrated via simulation studies and applications to real data…”
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    Journal Article
  9. 9

    Functional clustering of varved lake sediment to reconstruct past seasonal climate by Arnqvist, Per, Bigler, Christian, Renberg, Ingemar, Sjöstedt de Luna, Sara

    ISSN: 1352-8505, 1573-3009, 1573-3009
    Published: New York Springer US 01.12.2016
    Published in Environmental and ecological statistics (01.12.2016)
    “… and within-year seasonal patterns. We propose to use functional data analysis methods to extract the relevant information with respect to climate reconstruction from the rich but complex information in the varves, including the shapes…”
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    Journal Article
  10. 10
  11. 11

    Clustering Functional Data Based on Amplitude-Phase Separation by Zang, Xiao

    ISBN: 9798496561327
    Published: ProQuest Dissertations & Theses 01.01.2021
    “… The first method which we call elastic K-means extends its counterpart for multivariate data using an elastic metric that extracts the amplitude differences between functions and cluster templates…”
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    Dissertation