Relevant bibliographies by topics / Matrice de scatterplots

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Matrice de scatterplots'

Author: Grafiati
Published: 4 June 2021
Last updated: 5 February 2022

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Journal articles on the topic "Matrice de scatterplots"

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Foreman-Mackey, Daniel. "corner.py: Scatterplot matrices in Python." Journal of Open Source Software 1, no. 2 (2016): 24. http://dx.doi.org/10.21105/joss.00024.

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Lehmann, Dirk J., Georgia Albuquerque, Martin Eisemann, Marcus Magnor, and Holger Theisel. "Selecting Coherent and Relevant Plots in Large Scatterplot Matrices." Computer Graphics Forum 31, no. 6 (2012): 1895–908. http://dx.doi.org/10.1111/j.1467-8659.2012.03069.x.

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Riehmann, P., G. Molina León, J. Reibert, F. Echtler, and B. Froehlich. "Short‐Contact Touch‐Manipulation of Scatterplot Matrices on Wall Displays." Computer Graphics Forum 39, no. 3 (2020): 265–76. http://dx.doi.org/10.1111/cgf.13979.

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Pérez-Messina, Ignacio, Eduardo Graells-Garrido, María Jesús Lobo, and Christophe Hurter. "Modalflow: Cross-Origin Flow Data Visualization for Urban Mobility." Algorithms 13, no. 11 (2020): 298. http://dx.doi.org/10.3390/a13110298.

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Pervasive data have become a key source of information for mobility and transportation analyses. However, as a secondary source, it has a different methodological origin than travel survey data, usually relying on unsupervised algorithms, and so it requires to be assessed as a dataset. This assessment is challenging, because, in general, there is not a benchmark dataset or a ground truth scenario available, as travel surveys only represent a partial view of the phenomenon and suffer from their own biases. For this critical task, which involves urban planners and data scientists, we study the d
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Balash, Vladimir, Olga Balash, Alexey Faizliev, and Elena Chistopolskaya. "Economic Growth Patterns: Spatial Econometric Analysis for Russian Regions." Information 11, no. 6 (2020): 289. http://dx.doi.org/10.3390/info11060289.

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In this article, we analyze the σ - and β -convergence, using the data of the socio-economic development of Russian areas, and discover the role of spatial autocorrelation in regional economic development. We are considering 80 areas of the Russian Federation for the period of 2010–2017. Moran coefficients were used to estimate spatial autocorrelation. We compare the Moran scatterplots for GDP per capita and GDP growth rates per capita in 2017 and in 2014. We study the impact on raising investment in leading capital and the costs of technological innovation. We evaluate a wide range of specifi
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Leporcq, Clémentine, Yannick Spill, Delphine Balaramane, Christophe Toussaint, Michaël Weber, and Anaïs Flore Bardet. "TFmotifView: a webserver for the visualization of transcription factor motifs in genomic regions." Nucleic Acids Research 48, W1 (2020): W208—W217. http://dx.doi.org/10.1093/nar/gkaa252.

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Abstract Transcription factors (TFs) regulate the expression of gene expression. The binding specificities of many TFs have been deciphered and summarized as position-weight matrices, also called TF motifs. Despite the availability of hundreds of known TF motifs in databases, it remains non-trivial to quickly query and visualize the enrichment of known TF motifs in genomic regions of interest. Towards this goal, we developed TFmotifView, a web server that allows to study the distribution of known TF motifs in genomic regions. Based on input genomic regions and selected TF motifs, TFmotifView p
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Van Vliet, Martin H., Rowan Kuiper, Belinda Dumee, et al. "Single Sample Application of the EMC92/SKY92 Signature Using the Mmprofiler." Blood 124, no. 21 (2014): 2026. http://dx.doi.org/10.1182/blood.v124.21.2026.2026.

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Abstract Introduction Multiple Myeloma (MM) is a heterogeneous disease with diverse gene expression patterns (GEP) across patients. This has led to the development of various signatures allowing virtual karyotyping, defining different clusters of patients, and prognostication by high risk signatures (e.g. EMC92/SKY92). Several GEP datasets exist, but may have scaling/offset differences (batch effects) in the data, e.g. due to differences in reagents used, location, etc. Batch wise normalization approaches can reduce batch effects, and have allowed successful validation of those signatures acro
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Hauben, Manfred, Eric Hung, and Wen-Yaw Hsieh. "An exploratory factor analysis of the spontaneous reporting of severe cutaneous adverse reactions." Therapeutic Advances in Drug Safety 8, no. 1 (2016): 4–16. http://dx.doi.org/10.1177/2042098616670799.

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Background: Severe cutaneous adverse reactions (SCARs) are prominent in pharmacovigilance (PhV). They have some commonalities such as nonimmediate nature and T-cell mediation and rare overlap syndromes have been documented, most commonly involving acute generalized exanthematous pustulosis (AGEP) and drug rash with eosinophilia and systemic symptoms (DRESS), and DRESS and toxic epidermal necrolysis (TEN). However, they display diverse clinical phenotypes and variations in specific T-cell immune response profiles, plus some specific genotype–phenotype associations. A question is whether causati
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Milutinović, Goran, Ulla Ahonen-Jonnarth, and Stefan Seipel. "Does visual saliency affect decision-making?" Journal of Visualization, June 11, 2021. http://dx.doi.org/10.1007/s12650-021-00760-4.

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Abstract In the present study, we explore potential effects of visual saliency on decision quality in context of multi-criteria decision-making (MCDM). We compare two visualization techniques: parallel coordinates (PC) and scatterplot matrices (SPM). We investigate the impact of saliency facilitated by means of either color or size. The saliency and visualization techniques were factors in our analysis, and effects were evaluated in terms of decision quality, attention, time on task, and confidence. Results show that the quality of choice and attention were comparable for all saliency conditio
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Dissertations / Theses on the topic "Matrice de scatterplots"

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Aupetit, Sébastien. "Contributions aux Modèles de Markov Cachés : métaheuristiques d'apprentissage, nouveaux modèles et visualisation de dissimilarité." Phd thesis, Université François Rabelais - Tours, 2005. http://tel.archives-ouvertes.fr/tel-00168392.

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Dans ce travail de thèse, nous présentons plusieurs contributions visant à améliorer l'utilisation des modèles de Markov cachés (MMC) dans les systèmes d'intelligence artificielle. Nous nous sommes concentrés sur trois objectifs : l'amélioration de l'apprentissage de MMC, l'expérimentation d'un nouveau type de MMC et la visualisation de dissimilarité pour mieux comprendre les interactions entre MMC. Dans la première partie, nous proposons, évaluons et comparons plusieurs nouvelles applications<br />de métaheuristiques biomimétiques classiques (les algorithmes génétiques, l'algorithme de fourmi
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Yang, Jing. "Visual hierarchical dimension reduction." Link to electronic thesis, 2002. http://www.wpi.edu/Pubs/ETD/Available/etd-0109102-132821.

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Thesis (M.S.)--Worcester Polytechnic Institute.<br>Keywords: hierarchy; sunburst; dimension reduction; high dimensional data set; multidimensional visualization; parallel coordinates; scatterplot matrices; star glyphs. Includes bibliographical references (p. 86-91).
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Book chapters on the topic "Matrice de scatterplots"

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Van Long, Tran. "iSPLOM: Interactive with Scatterplot Matrix for Exploring Multidimensional Data." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-02741-8_16.

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Jourdan, Fabien, Alain Paris, Pierre-Yves Koenig, and Guy Melançon. "Multiscale Scatterplot Matrix for Visual and Interactive Exploration of Metabonomic Data." In Pixelization Paradigm. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-71027-1_18.

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Calero Valdez, André, Sascha Gebhardt, Torsten W. Kuhlen, and Martina Ziefle. "Measuring Insight into Multi-dimensional Data from a Combination of a Scatterplot Matrix and a HyperSlice Visualization." In Digital Human Modeling. Applications in Health, Safety, Ergonomics, and Risk Management: Health and Safety. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58466-9_21.

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"Scatterplot Matrices." In An Introduction to Regression Graphics. John Wiley & Sons, Inc., 2008. http://dx.doi.org/10.1002/9780470316863.ch4.

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"SAS Macro to Produce Scatterplot Matrices." In Handbook of Statistical Analyses Using SAS, Second Edition. Chapman and Hall/CRC, 2001. http://dx.doi.org/10.1201/9781420057553.axa.

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"Gary White Explains How to Create a Scatterplot Matrix Using Seaborn in Matplotlib." In Scatter Plot Matrix. Gary White, 2020. http://dx.doi.org/10.4135/9781529772739.n1.

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Conference papers on the topic "Matrice de scatterplots"

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Chen, Helen, Sophie Engle, Alark Joshi, Eric D. Ragan, Beste F. Yuksel, and Lane Harrison. "Using Animation to Alleviate Overdraw in Multiclass Scatterplot Matrices." In CHI '18: CHI Conference on Human Factors in Computing Systems. ACM, 2018. http://dx.doi.org/10.1145/3173574.3173991.

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Cui, Qingguang, Matthew O. Ward, and Elke A. Rundensteiner. "Enhancing scatterplot matrices for data with ordering or spatial attributes." In Electronic Imaging 2006, edited by Robert F. Erbacher, Jonathan C. Roberts, Matti T. Gröhn, and Katy Börner. SPIE, 2006. http://dx.doi.org/10.1117/12.650409.

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