- Išparduota
/https://libri-media.knygos-static.lt/cd5c14cd-93c0-4d08-a721-a4f00dfb5ccc/1)
- Autorius: Xizhao Wang, Junhai Zhai
- Leidėjas: Taylor & Francis Ltd.
- Metai: 2016
- Puslapiai: 239
- ISBN: 9781315353562
- ISBN-10: 1315353563
- ISBN-13: 9781315353562
- Formatas: ACSM ?
- Kalba: Anglų
Atsiliepimai
Formatai:
Aprašymas
Learning with uncertainty covers a broad range of scenarios in machine learning, this book mainly focuses on: (1) Decision tree learning with uncertainty, (2) Clustering under uncertainty environment, (3) Active learning based on uncertainty criterion, and (4) Ensemble learning in a framework of uncertainty. The book starts with the introduction to uncertainty including randomness, roughness, fuzziness and non-specificity and then comprehensively discusses a number of key issues in learning with uncertainty, such as uncertainty representation in learning, the influence of uncertainty on the performance of learning system, the heuristic design with uncertainty, etc.
Most contents of the book are our research results in recent decades. The purpose of this book is to help the readers to understand the impact of uncertainty on learning processes. It comes with many examples to facilitate understanding. The book can be used as reference book or textbook for researcher fellows, senior undergraduates and postgraduates majored in computer science and technology, applied mathematics, automation, electrical engineering, etc.
Elektroninė knyga:
Atsiuntimas po užsakymo akimirksniu! Skirta skaitymui tik kompiuteryje, planšetėje ar kitame elektroniniame įrenginyje.
Kaip skaityti el. knygas ACSM formatu?
Mažiausia kaina per 30 dienų: 99,99 €
Mažiausia kaina užfiksuota: 2026-06-03 03:33:15
- Autorius: Xizhao Wang, Junhai Zhai
- Leidėjas: Taylor & Francis Ltd.
- Metai: 2016
- Puslapiai: 239
- ISBN: 9781315353562
- ISBN-10: 1315353563
- ISBN-13: 9781315353562
- Formatas: ACSM ?
- Kalba: Anglų
Learning with uncertainty covers a broad range of scenarios in machine learning, this book mainly focuses on: (1) Decision tree learning with uncertainty, (2) Clustering under uncertainty environment, (3) Active learning based on uncertainty criterion, and (4) Ensemble learning in a framework of uncertainty. The book starts with the introduction to uncertainty including randomness, roughness, fuzziness and non-specificity and then comprehensively discusses a number of key issues in learning with uncertainty, such as uncertainty representation in learning, the influence of uncertainty on the performance of learning system, the heuristic design with uncertainty, etc.
Most contents of the book are our research results in recent decades. The purpose of this book is to help the readers to understand the impact of uncertainty on learning processes. It comes with many examples to facilitate understanding. The book can be used as reference book or textbook for researcher fellows, senior undergraduates and postgraduates majored in computer science and technology, applied mathematics, automation, electrical engineering, etc.
Atsiliepimai