Bemærk: Kan ikke leveres før jul.
This book provides an introduction to the field of periodic pattern mining, reviews state-of-the-art techniques, discusses recent advances, and reviews open-source software.
Bemærk: Kan ikke leveres før jul.
This book introduces readers to an evolutionary learning approach, specifically genetic programming (GP), for production scheduling. In Part I, it provides an introduction to production scheduling, existing solution methods, and the GP approach to production scheduling.
Bemærk: Kan ikke leveres før jul.
It features a range of proven and recent nature-inspired algorithms used to data clustering, including particle swarm optimization, ant colony... Læs mere
Bemærk: Kan ikke leveres før jul.
Bemærk: Kan ikke leveres før jul.
This book sets the stage of the evolution of corporate governance, laws and regulations, other forms of governance, and the interaction between data governance and other corporate governance sub-disciplines.
Bemærk: Kan ikke leveres før jul.
Bemærk: Kan ikke leveres før jul.
Bemærk: Kan ikke leveres før jul.
This insight has led to an embryonic stage of new theorizing, empirical research, and the formation of new technologies, standards, practices, and concepts to ensure the availability of adequate 'paradata' – data on the making and processing of data.
Bemærk: Kan ikke leveres før jul.
This book focuses on Entity Discovery and Linking (EDL), which is the problem of identifying concepts and entities, disambiguating them, and grounding them to one or more... Læs mere
Bemærk: Kan ikke leveres før jul.
This popular book, updated as a textbook for classroom use, discusses text mining and different ways this type of data mining can be used to... Læs mere
Bemærk: Kan ikke leveres før jul.
This updated book describes optimization models of clustering problems and clustering algorithms based on optimization techniques, including their implementation, evaluation, and applications.
Bemærk: Kan ikke leveres før jul.
This is where the principle of “Informed Machine Learning” comes into play.Informed Machine Learning combines purely data driven learning and knowledge-based techniques to learn from both data and knowledge.