Isbn: 9783319697741 - towards integrative machine learning and knowledge extraction: birs workshop, banff, ab, canada, july 24-26, 2015, revised selected papers: 10344 (17 risultati)

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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The BIRS Workshop 'Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets' (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of 'hot topics' toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain. The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.…

Taschenbuch. Condizione: Neu. Towards Integrative Machine Learning and Knowledge Extraction | BIRS Workshop, Banff, AB, Canada, July 24-26, 2015, Revised Selected Papers | Andreas Holzinger (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xvi | Englisch | 2017 | Springer | EAN 9783319697741 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The BIRS Workshop 'Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets' (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of 'hot topics' toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain. The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning. 224 pp. Englisch.…

Condizione: New. Print on Demand pp. 207.

Condizione: New. PRINT ON DEMAND pp. 207.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The BIRS Workshop ¿Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets¿ (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of ¿hot topics¿ toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain.The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 224 pp. Englisch.…