Sarah Vluymans – författare

Visar alla böcker från författaren Sarah Vluymans. Handla med fri frakt och snabb leverans.

5 produkter

1. 

   Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods

   Av Sarah Vluymans

   Inbunden, 2018

   1127 kr

   Lägg i varukorg

   This book presents novel classification algorithms for four challenging prediction tasks, namely learning from imbalanced, semi-supervised, multi-instance and multi-label data. The methods are based on fuzzy rough set theory, a mathematical framework used to model uncertainty in data. The book …

2. 

   Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods

   Av Sarah Vluymans

   E-bok, 2018

   1470 kr

   Lägg i varukorg

   This book presents novel classification algorithms for four challenging prediction tasks, namely learning from imbalanced, semi-supervised, multi-instance and multi-label data. The methods are based on fuzzy rough set theory, a mathematical framework used to model uncertainty in data. The book …

3. 

   Multiple Instance Learning

   Foundations and Algorithms

   Av Francisco Herrera, Sebastián Ventura m. fl.

   Inbunden, 2016

   1131 kr

   Lägg i varukorg

   This book provides a general overview of multiple instance learning (MIL), defining the framework and covering the central paradigms. The authors discuss the most important algorithms for MIL such as classification, regression and clustering. With a focus on classification, a taxonomy is set and …

4. 

   Multiple Instance Learning

   Foundations and Algorithms

   Av Sarah Vluymans, Danel Sanchez-Tarrago m. fl.

   E-bok, 2016

   1470 kr

   Lägg i varukorg

   This book provides a general overview of multiple instance learning (MIL), defining the framework and covering the central paradigms. The authors discuss the most important algorithms for MIL such as classification, regression and clustering. With a focus on classification, a taxonomy is set and …

5. 

   Multiple Instance Learning

   Foundations and Algorithms

   Av Francisco Herrera, Sebastián Ventura m. fl.

   Häftad, 2018

   1131 kr

   Lägg i varukorg

   This book provides a general overview of multiple instance learning (MIL), defining the framework and covering the central paradigms. The authors discuss the most important algorithms for MIL such as classification, regression and clustering. With a focus on classification, a taxonomy is set and …