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1. |
Record Nr. |
UNINA9910741146803321 |
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Autore |
Liu Han |
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Titolo |
Rule Based Systems for Big Data : A Machine Learning Approach / / by Han Liu, Alexander Gegov, Mihaela Cocea |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (127 p.) |
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Collana |
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Studies in Big Data, , 2197-6503 ; ; 13 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Artificial intelligence |
Data mining |
Computational Intelligence |
Artificial Intelligence |
Data Mining and Knowledge Discovery |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters. |
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Nota di contenuto |
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Introduction -- Theoretical Preliminaries -- Generation of Classification Rules -- Simplification of Classification Rules -- Representation of Classification Rules -- Ensemble Learning Approaches -- Interpretability Analysis. |
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Sommario/riassunto |
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The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems. |
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2. |
Record Nr. |
UNINA9911020036703321 |
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Autore |
Raj Balwinder |
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Titolo |
FeFET Devices, Trends, Technology and Applications |
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Pubbl/distr/stampa |
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Newark : , : John Wiley & Sons, Incorporated, , 2025 |
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©2025 |
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ISBN |
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9781394287307 |
1394287305 |
9781394287284 |
1394287283 |
9781394287291 |
1394287291 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (353 pages) |
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Collana |
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Semiconductor devices and their applications |
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Altri autori (Persone) |
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RahiShiromani Balmukund |
YadavNandakishor |
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Disciplina |
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Soggetti |
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Field-effect transistors |
Ferroelectric devices |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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FeFET Devices, Trends, Technology and Applications is essential for anyone seeking an in-depth understanding of the latest advancements in ferroelectric devices, as it offers comprehensive insights into research techniques, novel materials, and the historical context of semiconductor development. This book serves as an encyclopedia of knowledge for state-of-the-art research techniques for the miniaturization of ferroelectric devices. This volume explores characteristics, novel materials used, modifications in device structure, and advancements in model FET devices. Though many devices following Moore's Law and More-Moore are proposed, a complete history of existing and proposed semiconductor devices is now available here. This resource focuses on developments and research in emerging ferroelectric FET devices and their applications, providing unique coverage of topics covering recent advancements and novel |
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concepts in the field of miniaturized ferroelectric devices. |
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