machine learning knowledge extraction (105 Ergebnisse)

Zustand: Very Good. Most items will be dispatched the same or the next working day. A copy that has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Kartoniert / Broschiert. Zustand: New.

Kartoniert / Broschiert. Zustand: New.

Taschenbuch. Zustand: Neu. Neuware -This book constitutes the refereed proceedings of the IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2018, held in Hamburg, Germany, in September 2018.The 25 revised full papers presented were carefully reviewed and selected from 45 submissions. The papers are clustered under the following topical sections: MAKE-Main Track, MAKE-Text, MAKE-Smart Factory, MAKE-Topology, and MAKE Explainable AI.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 388 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware -This book constitutes the refereed proceedings of the IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2017, held in Reggio, Italy, in August/September 2017.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 392 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware -This book is proposing a hybrid algorithm of two fuzzy genetic-based machine learning approaches - Michigan and Pittsburgh - for designing fuzzy rule-based classification systems. The search ability of each approach is examined to efficiently find fuzzy rule-based systems with high classification accuracy. These two approaches are combined into a single hybrid algorithm. The generalization ability of fuzzy rule-based classification systems, designed by the proposed hybrid algorithm is examined on real data sets. Experimental results show that the hybrid algorithm has higher search ability within a population of individual rules and within a population of rule sets.Books on Demand GmbH, Überseering 33, 22297 Hamburg 140 pp. Englisch.

Paperback. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 1.72.

Taschenbuch. Zustand: Neu. Neuware -This book constitutes the refereed proceedings of the 6th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2022, held in Vienna, Austria during August 2022.The 23 full papers presented were carefully reviewed and selected from 45 submissions. The papers are covering a wide range from integrative machine learning approach, considering the importance of data science and visualization for the algorithmic pipeline with a strong emphasis on privacy, data protection, safety and security.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 392 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware -This book constitutes the refereed proceedings of the 5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2021, held in virtually in August 2021.The 20 full papers and 2 short papers presented were carefully reviewed and selected from 48 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 376 pp. Englisch.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - It is becoming increasingly important to understand the possible cause and effect relationships between these solar events and features to produce timely and reliable computer-based forecasting of extreme solar events. These forecasts are very important for protecting our technological infra-structures and human life on earth and in space. The need to develop automated tools to process solar data is also increasing because existing space missions are sending huge amounts of data and scientists back on Earth are struggling to keep pace. In this book, we present our research work introducing novel, fully computerised, machine learning-based decision rules and models that can be used within a system design for automated space weather forecasting. The system design in this book consists of three stages: (1) designing computer tools to find the associations among solar events and features (2) applying machine learning algorithms to the associations datasets and (3) studying the evolution patterns of sunspot groups using time-series methods.