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pro vyhledávání: '"Ventocilla, Elio"'
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In Big Data Research 15 November 2021 26
Autor:
Ventocilla, Elio
Swarm Intelligence (SI) is a young field of study from which solutions to complex problems have been proposed based on how some natural organisms (e.g. ants, bees and others) achieve many of their daily tasks through simple sets of interactions. This
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-212190
Autor:
Ventocilla, Elio
Large quantities of data are being collected and analyzed by companies and institutions, with the aim of extracting knowledge and value. When little is known about the data at hand, analysts engage in exploratory data analysis to achieve a better und
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https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::6ed3e1435ece1016c1199235cdc9f551
http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19458
http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19458
Autor:
Ventocilla, Elio, Riveiro, Maria
Supplemental material, Supplementary_material for A comparative user study of visualization techniques for cluster analysis of multidimensional data sets by Elio Ventocilla and Maria Riveiro in Information Visualization
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https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2c6e2d480b74a86c99567a2c62771620
As large datasets become more common, so becomes the necessity for exploratory approaches that allow iterative, trial-anderror analysis. Without such solutions, hypothesis testing and exploratory data analysis may become cumbersome due to long waitin
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https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c01d4861fac218af07813d2f0e4b1301
http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19461
http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19461
Akademický článek
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Autor:
Ventocilla, Elio
Large quantities of data are being collected and analyzed by companies and institutions, with the intention of drawing knowledge and value. Advances in storage, computation, automated analysis and visual and interactive techniques have facilitated th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::605710638711c3b1a216e6e0b5e661ac
http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-16931
http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-16931
Autor:
Ventocilla, Elio, Helldin, Tove, Riveiro, Maria, Bae, Juhee, Boeva, Veselka, Falkman, Göran, Lavesson, Niklas
We propose a taxonomy for classifying and describing papers which contribute to making Machine Learning (ML) techniques interactive and interpretable for users. The taxonomy is composed of six elements – Dataset, Optimizer, Model, Predictions, Eval
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6e7b5d34574c0004a74846838a7c275d
http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19457
http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19457