Multiple Instance Learning (Record no. 56956)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03876nam a22005655i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-319-47759-6 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20200421112046.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 161108s2016 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783319477596 |
| -- | 978-3-319-47759-6 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.3 |
| 100 1# - AUTHOR NAME | |
| Author | Herrera, Francisco. |
| 245 10 - TITLE STATEMENT | |
| Title | Multiple Instance Learning |
| Sub Title | Foundations and Algorithms / |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XI, 233 p. 46 illus., 40 illus. in color. |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | 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. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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 most relevant proposals are specified. Efficient algorithms are developed to discover relevant information when working with uncertainty. Key representative applications are included. This book carries out a study of the key related fields of distance metrics and alternative hypothesis. Chapters examine new and developing aspects of MIL such as data reduction for multi-instance problems and imbalanced MIL data. Class imbalance for multi-instance problems is defined at the bag level, a type of representation that utilizes ambiguity due to the fact that bag labels are available, but the labels of the individual instances are not defined. Additionally, multiple instance multiple label learning is explored. This learning framework introduces flexibility and ambiguity in the object representation providing a natural formulation for representing complicated objects. Thus, an object is represented by a bag of instances and is allowed to have associated multiple class labels simultaneously. This book is suitable for developers and engineers working to apply MIL techniques to solve a variety of real-world problems. It is also useful for researchers or students seeking a thorough overview of MIL literature, methods, and tools. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Ventura, Sebasti�an. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Bello, Rafael. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Cornelis, Chris. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Zafra, Amelia. |
| 700 1# - AUTHOR 2 | |
| Author 2 | S�anchez-Tarrag�o, D�anel. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Vluymans, Sarah. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-319-47759-6 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2016. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer science. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Algorithms. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Image processing. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial Intelligence (incl. Robotics). |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Image Processing and Computer Vision. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Algorithm Analysis and Problem Complexity. |
| 912 ## - | |
| -- | ZDB-2-SCS |
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