Mohlo by se vám také líbit

Více informací o knize Feature Learning and Understanding

• Parametry knihy
• Anotace
• Oblíbené z jiného soudku

Nákupem získáte 338 bodů

Anotace knihy

This book covers the essential concepts and strategies within traditional and cutting-edge feature learning methods thru both theoretical analysis and case studies. Good features give good models and it is usually not classifiers but features that determine the effectiveness of a model. In this book, readers can find not only traditional feature learning methods, such as principal component analysis, linear discriminant analysis, and geometrical-structure-based methods, but also advanced feature learning methods, such as sparse learning, low-rank decomposition, tensor-based feature extraction, and deep-learning-based feature learning. Each feature learning method has its own dedicated chapter that explains how it is theoretically derived and shows how it is implemented for real-world applications. Detailed illustrated figures are included for better understanding. This book can be used by students, researchers, and engineers looking for a reference guide for popular methods of feature learning and machine intelligence.

Parametry knihy

Zařazení knihy Knihy v angličtině Society & social sciences Sociology & anthropology Sociology

• Plný název: Feature Learning and Understanding
• Podnázev: Algorithms and Applications
• Autor: Haitao Zhao, Zhihui Lai, Henry Leung, Xianyi Zhang
• Jazyk: Angličtina
• Vazba: Pevná
• Počet stran: 291
• EAN: 9783030407933
• ID: 25516996
• Nakladatelství: Springer Nature Switzerland AG
• Hmotnost: 629 g
• Rozměry: 235 × 155 × 22 mm
• Datum vydání: 04. April 2020

Oblíbené z jiného soudku

---

---

---