"Topological data analysis"의 두 판 사이의 차이

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* Topological data analysis (TDA) is an emerging concept of data analysis for characterizing shape of data.<ref name="ref_d7a3">[https://www.riken.jp/en/research/labs/aip/generic_tech/topology_data_anl/index.html Topological Data Analysis Team]</ref>
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===말뭉치===
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* Topological data analysis (TDA) is a field of mathematics which deals with qualitative geometric features to analyze datasets.<ref name="ref_8004">[https://www.indicative.com/data-defined/topological-data-analysis/ What Is Topological Data Analysis? Data Defined]</ref>
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# Topological data analysis (TDA) is an emerging concept of data analysis for characterizing shape of data.<ref name="ref_d7a3">[https://www.riken.jp/en/research/labs/aip/generic_tech/topology_data_anl/index.html Topological Data Analysis Team]</ref>
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* We demonstrate the utility of topological data analysis combined with MC and present its merits and disadvantages.<ref name="ref_3fbf">[https://onlinelibrary.wiley.com/doi/abs/10.1002/asmb.2563 Topological data analysis in digital marketing]</ref>
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# Topological data analysis (TDA) is a field of mathematics which deals with qualitative geometric features to analyze datasets.<ref name="ref_8004">[https://www.indicative.com/data-defined/topological-data-analysis/ What Is Topological Data Analysis? Data Defined]</ref>
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* The emerging area of topological data analysis (TDA) is a promising avenue of research to answer the challenge.<ref name="ref_0c95">[https://www.ibc2020.org/ibc2020/scientific-programme/shortcourses/sc07 Online Learning Series]</ref>
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# On this page I have a number of items to get the interested reader started with persistent homology and topological data analysis (TDA).<ref name="ref_37b6a0f0">[https://people.clas.ufl.edu/peterbubenik/intro-to-tda/ Topological Data Analysis]</ref>
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* Chung is a leading expert of Topological Data analysis and has published more than 20 peer reviewed papers on this topic.<ref name="ref_0c95" />
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# In topological data analysis, one usually replaces the original space with one or more topological spaces that one hopes will retain the relevant topological information in the original set.<ref name="ref_0acb0af5">[https://www.imsi.institute/activities/topological-data-analysis/ Topological Data Analysis • IMSI]</ref>
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* Wang is a leading expert on Topological Data Analysis in signal processing, particularly in electroencephalographic signals.<ref name="ref_0c95" />
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# In applied mathematics, topological data analysis (TDA) is an approach to the analysis of datasets using techniques from topology.<ref name="ref_f64311da">[https://en.wikipedia.org/wiki/Topological_data_analysis Topological data analysis]</ref>
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* The newly-emerging domain comprising topology-based techniques is often referred to as topological data analysis (TDA).<ref name="ref_5fe9">[https://tda-in-ml.github.io/ Topological Data Analysis and Beyond]</ref>
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# Topological data analysis (tda) is a recent and fast-growing field providing a set of new topological and geometric tools to infer relevant features for possibly complex data.<ref name="ref_6861ec47">[https://www.frontiersin.org/articles/10.3389/frai.2021.667963/full An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists]</ref>
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* In applied mathematics, topological data analysis (TDA) is an approach to the analysis of datasets using techniques from topology.<ref name="ref_f643">[https://en.wikipedia.org/wiki/Topological_data_analysis Topological data analysis]</ref>
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# Statistical topological data analysis using persistence landscapes.<ref name="ref_bb5e6fa3">[https://learning-analytics.info/index.php/JLA/article/view/5196 A User’s Guide to Topological Data Analysis]</ref>
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* One way to apply statistics to topological data analysis is to study the statistical properties of topological features of point clouds.<ref name="ref_f643" />
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# Abstract We apply tools from topological data analysis to two mathematical models inspired by biological aggregations such as bird flocks, fish schools, and insect swarms.<ref name="ref_821e2c82">[https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0126383 Topological Data Analysis of Biological Aggregation Models]</ref>
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* Topological data analysis and persistent homology have had impacts on Morse theory.<ref name="ref_f643" />
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# In brief, we use the methods of topological data analysis to compute the persistent homology of spatiotemporal aggregation data sets arising from numerical simulation of models.<ref name="ref_821e2c82" />
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* Towards a new approach to reveal dynamical organization of the brain using topological data analysis.<ref name="ref_033e">[https://www.frontiersin.org/articles/10.3389/fams.2020.00034/full Topological Data Analysis of Vascular Disease: A Theoretical Framework]</ref>
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# Our primary goal is to demonstrate the utility of topological data analysis for biological aggregations and similar applications.<ref name="ref_821e2c82" />
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* But around this same time I kept hearing about an exciting but possibly over-hyped topic called topological data analysis: TDA.<ref name="ref_a0f6">[https://rviews.rstudio.com/2018/11/14/a-mathematician-s-perspective-on-topological-data-analysis-and-r/ A Mathematician's Perspective on Topological Data Analysis and R]</ref>
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# We combine topological data analysis and machine learning to provide a collection of summary statistics describing patterns on both microscopic and macroscopic scales.<ref name="ref_dd596447">[https://www.pnas.org/content/117/10/5113 Topological data analysis of zebrafish patterns]</ref>
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* In this article, I’ll specifically break down what Topological Data Analysis is and how to think about it.<ref name="ref_cfd6">[https://towardsdatascience.com/topological-data-analysis-unpacking-the-buzzword-2fab3bb63120 Topological Data Analysis — Unpacking the Buzzword]</ref>
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# Here we introduce methods based on topological data analysis and interpretable machine learning for quantifying both agent-level features and global pattern attributes on a large scale.<ref name="ref_dd596447" />
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* How is Topology related to Topological Data Analysis?<ref name="ref_cfd6" />
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# 27, topological data analysis (TDA) has emerged as a valuable tool for characterizing collective behavior and self-organization.<ref name="ref_dd596447" />
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* These aspects are all essential in the field of Persistent Homology, which is the main tool that Topological Data Analysis is inspired by.<ref name="ref_cfd6" />
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# The newly-emerging domain comprising topology-based techniques is often referred to as topological data analysis (TDA).<ref name="ref_5fe90793">[https://tda-in-ml.github.io/ Topological Data Analysis and Beyond]</ref>
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* Topological data analysis reveals the structure of data.<ref name="ref_9e88">[https://www.cambridge.org/core/books/topological-data-analysis-for-genomics-and-evolution/FCC8429FAD2B5D1525AEA47A8366D6EB Topological Data Analysis for Genomics and Evolution]</ref>
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# But around this same time I kept hearing about an exciting but possibly over-hyped topic called topological data analysis: TDA.<ref name="ref_a0f621f5">[https://rviews.rstudio.com/2018/11/14/a-mathematician-s-perspective-on-topological-data-analysis-and-r/ A Mathematician's Perspective on Topological Data Analysis and R]</ref>
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* This is a very important work that shows the way to applications of topological data analysis in genomics.<ref name="ref_9e88" />
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# One of the key messages around topological data analysis is that data has shape and the shape matters.<ref name="ref_046650b0">[https://www.indicative.com/resource/topological-data-analysis/ What Is Topological Data Analysis? Data Defined]</ref>
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* 27, topological data analysis (TDA) has emerged as a valuable tool for characterizing collective behavior and self-organization.<ref name="ref_396d">[https://www.pnas.org/content/117/10/5113 Topological data analysis of zebrafish patterns]</ref>
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# What is topological data analysis (TDA), and why is TDA taking the big data world by storm?<ref name="ref_427229b6">[https://www.ayasdi.com/social/TDAintroduction/ Introduction to Topological Data Analysis]</ref>
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# Introduction Topological data analysis (TDA) consists of a growing set of methods that provide insight to the shape of data (see the surveys Ghrist, 2008; Carlsson, 2009).<ref name="ref_f57917da">[https://www.jmlr.org/papers/volume16/bubenik15a/bubenik15a.pdf Journal of machine learning research 16 (2015) 77-102]</ref>
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# Topological data analysis (TDA) involves extracting information from clouds of data points and using the information to classify data, recognize patterns or predict trends, for example.<ref name="ref_c3a618e5">[https://actu.epfl.ch/news/topological-data-analysis-can-help-predict-crashes/ Topological data analysis can help predict crashes]</ref>
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# Introduction Topological data analysis (TDA) describes the shape of noisy and potentially incomplete data in a robust way, so that such data can be better understood and utilised.<ref name="ref_ee8f29ef">[https://www.turing.ac.uk/research/research-projects/scalable-topological-data-analysis Scalable topological data analysis]</ref>
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# The development of this software will enable researchers at the Turing and elsewhere to apply topological data analysis at a previously unachievable scale.<ref name="ref_ee8f29ef" />
 +
# It will also lead to the development of new techniques that make topological data analysis more robust to the presence of egregious outliers in large datasets.<ref name="ref_ee8f29ef" />
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# In this paper, we present an alternative approach to AR pattern recognition based on topological data analysis (TDA) (Ghrist, 2008; Carlsson, 2009, 2014) and machine learning (ML) (Kubat, 2015).<ref name="ref_ccea9246">[https://gmd.copernicus.org/articles/12/613/2019/ Topological data analysis and machine learning for recognizing atmospheric river patterns in large climate datasets]</ref>
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# Topological data analysis (TDA) aims to measure the “intrinsic shape” of data and identify this manifold despite noise and the likely nonlinear embedding.<ref name="ref_2466419d">[https://www.broadinstitute.org/talks/topological-data-analysis-what-persistent-homology Topological data analysis: What is persistent homology?]</ref>
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# Topological data analysis reveals the structure of data.<ref name="ref_9e884c7e">[https://www.cambridge.org/core/books/topological-data-analysis-for-genomics-and-evolution/FCC8429FAD2B5D1525AEA47A8366D6EB Topological Data Analysis for Genomics and Evolution]</ref>
 
===소스===
 
===소스===
 
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* ID :  [https://www.wikidata.org/wiki/Q4460773 Q4460773]
 
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===Spacy 패턴 목록===
 
* [{'LOWER': 'topological'}, {'LOWER': 'data'}, {'LEMMA': 'analysis'}]
 
* [{'LOWER': 'topological'}, {'LOWER': 'data'}, {'LEMMA': 'analysis'}]

2021년 10월 19일 (화) 00:45 기준 최신판

노트

말뭉치

  1. Topological data analysis (TDA) is an emerging concept of data analysis for characterizing shape of data.[1]
  2. Topological data analysis (TDA) is a field of mathematics which deals with qualitative geometric features to analyze datasets.[2]
  3. On this page I have a number of items to get the interested reader started with persistent homology and topological data analysis (TDA).[3]
  4. In topological data analysis, one usually replaces the original space with one or more topological spaces that one hopes will retain the relevant topological information in the original set.[4]
  5. In applied mathematics, topological data analysis (TDA) is an approach to the analysis of datasets using techniques from topology.[5]
  6. Topological data analysis (tda) is a recent and fast-growing field providing a set of new topological and geometric tools to infer relevant features for possibly complex data.[6]
  7. Statistical topological data analysis using persistence landscapes.[7]
  8. Abstract We apply tools from topological data analysis to two mathematical models inspired by biological aggregations such as bird flocks, fish schools, and insect swarms.[8]
  9. In brief, we use the methods of topological data analysis to compute the persistent homology of spatiotemporal aggregation data sets arising from numerical simulation of models.[8]
  10. Our primary goal is to demonstrate the utility of topological data analysis for biological aggregations and similar applications.[8]
  11. We combine topological data analysis and machine learning to provide a collection of summary statistics describing patterns on both microscopic and macroscopic scales.[9]
  12. Here we introduce methods based on topological data analysis and interpretable machine learning for quantifying both agent-level features and global pattern attributes on a large scale.[9]
  13. 27, topological data analysis (TDA) has emerged as a valuable tool for characterizing collective behavior and self-organization.[9]
  14. The newly-emerging domain comprising topology-based techniques is often referred to as topological data analysis (TDA).[10]
  15. But around this same time I kept hearing about an exciting but possibly over-hyped topic called topological data analysis: TDA.[11]
  16. One of the key messages around topological data analysis is that data has shape and the shape matters.[12]
  17. What is topological data analysis (TDA), and why is TDA taking the big data world by storm?[13]
  18. Introduction Topological data analysis (TDA) consists of a growing set of methods that provide insight to the shape of data (see the surveys Ghrist, 2008; Carlsson, 2009).[14]
  19. Topological data analysis (TDA) involves extracting information from clouds of data points and using the information to classify data, recognize patterns or predict trends, for example.[15]
  20. Introduction Topological data analysis (TDA) describes the shape of noisy and potentially incomplete data in a robust way, so that such data can be better understood and utilised.[16]
  21. The development of this software will enable researchers at the Turing and elsewhere to apply topological data analysis at a previously unachievable scale.[16]
  22. It will also lead to the development of new techniques that make topological data analysis more robust to the presence of egregious outliers in large datasets.[16]
  23. In this paper, we present an alternative approach to AR pattern recognition based on topological data analysis (TDA) (Ghrist, 2008; Carlsson, 2009, 2014) and machine learning (ML) (Kubat, 2015).[17]
  24. Topological data analysis (TDA) aims to measure the “intrinsic shape” of data and identify this manifold despite noise and the likely nonlinear embedding.[18]
  25. Topological data analysis reveals the structure of data.[19]

소스

  1. ↑ Topological Data Analysis Team
  2. ↑ What Is Topological Data Analysis? Data Defined
  3. ↑ Topological Data Analysis
  4. ↑ Topological Data Analysis • IMSI
  5. ↑ Topological data analysis
  6. ↑ An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists
  7. ↑ A User’s Guide to Topological Data Analysis
  8. ↑ 8.0 8.1 8.2 Topological Data Analysis of Biological Aggregation Models
  9. ↑ 9.0 9.1 9.2 Topological data analysis of zebrafish patterns
  10. ↑ Topological Data Analysis and Beyond
  11. ↑ A Mathematician's Perspective on Topological Data Analysis and R
  12. ↑ What Is Topological Data Analysis? Data Defined
  13. ↑ Introduction to Topological Data Analysis
  14. ↑ Journal of machine learning research 16 (2015) 77-102
  15. ↑ Topological data analysis can help predict crashes
  16. ↑ 16.0 16.1 16.2 Scalable topological data analysis
  17. ↑ Topological data analysis and machine learning for recognizing atmospheric river patterns in large climate datasets
  18. ↑ Topological data analysis: What is persistent homology?
  19. ↑ Topological Data Analysis for Genomics and Evolution

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