Ergebnisse für: Multi-Label Learning

Hier findest Du Bücher, die sich mit Multi-Label Learning beschäftigen.

Buch Cover Multi-objective, Multi-class and Multi-label Data Classification with Class Imbalance
Multi-objective, Multi-class and Multi-label Data Classification with Class Imbalance
Sanjay Chakraborty, Lopamudra Dey
Springer Singapore
192.59 € · Hardcover
Supervised Learning Classification Multi-Objective Multi-class Multi-Label Machine Learning Deep Learning Artificial Intelligence Class Imbalance
This book explores intricate world of data classification with 'Multi-Objective, Multi-Class, and Multi-Label Data Classification.' This book studies sophisticated methods and strategies for working with complicated data sets, tackling the difficulties of various classes, many objectives, and compli...
Buch Cover Multiple Instance Learning
Multiple Instance Learning
Francisco Herrera, Sebastián Ventura, Rafael Bello, Chris Cornelis, Amelia Zafra, Dánel Sánchez-Tarragó, Sarah Vluymans
Springer International Publishing
106.99 € · Hardcover
Machine learning Data mining Multiple instance learning Multiple instance classification Multiple instance regression Multiple instance clustering Instance selection in multiple instance learning Dimensionality reduction Feature selection in multiple instance learning Multi-instance learning from imbalanced data Data reduction in multiple instance learning Multi-instance multi-label classification algorithm analysis and problem complexity
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...
Buch Cover Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods
Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods
Sarah Vluymans
Springer International Publishing
106.99 € · Hardcover
Computational Intelligence OWA Ordered Weighted Average Classification Multi-Instance Learning Multi-Label Learning
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 makes...
Buch Cover Multilabel Classification
Multilabel Classification
Francisco Herrera, Francisco Charte, Antonio J. Rivera, María J. del Jesus
Springer International Publishing
106.99 € · Hardcover
Data mining Machine learning Classification Multi-label data Text categorization Preprocessing Dataset characterization Learning from imbalanced data Dimensionality reduction Feature selection Data mining software
This book offers a comprehensive review of multilabel techniques widely used to classify and label texts, pictures, videos and music in the Internet. A deep review of the specialized literature on the field includes the available software needed to work with this kind of data. It provides the user w...
Buch Cover Predictive Clustering
Predictive Clustering
Hendrik Blockeel, Sašo Džeroski, Jan Struyf, Bernard Zenko
Springer US
80.2 € · Hardcover
Data mining Machine learning Predictive clustering analysis of remote sensing data bio-informatics classification clustering clustering time-series data eco-informatics ecological modeling environmental quality classification gene expression data analysis habitat modeling hierarchical classification learning algorithms
This book introduces a novel paradigm for machine learning and data mining called predictive clustering, which covers a broad variety of learning tasks and offers a fresh perspective on existing techniques. The book presents an informal introduction to predictive clustering, describing learning tas...
Buch Cover Multi-objective, Multi-class and Multi-label Data Classification with Class Imbalance
Multi-objective, Multi-class and Multi-label Data Classification with Class Imbalance
Sanjay Chakraborty, Lopamudra Dey
Springer Singapore
192.59 € · eBook
Supervised Learning Classification Multi-Objective Multi-class Multi-Label Machine Learning Deep Learning Artificial Intelligence Class Imbalance
This book explores intricate world of data classification with 'Multi-Objective, Multi-Class, and Multi-Label Data Classification.' This book studies sophisticated methods and strategies for working with complicated data sets, tackling the difficulties of various classes, many objectives, and compli...