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Multiple Instance Learning Foundations and Algorithms /
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 the...
| Call Number: | Libro Electrónico |
|---|---|
| Main Authors: | , , , , , , |
| Corporate Author: | |
| Format: | Electronic eBook |
| Language: | Inglés |
| Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2016.
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| Edition: | 1st ed. 2016. |
| Subjects: | |
| Online Access: | Texto Completo |
Table of Contents:
- Introduction
- Multiple Instance Learning
- Multi-Instance Classification
- Instance-Based Classification Methods
- Bag-Based Classification Methods
- Multi-Instance Regression
- Unsupervised Multiple Instance Learning
- Data Reduction
- Imbalance Multi-Instance Data
- Multiple Instance Multiple Label Learning.