Librería Portfolio Librería Portfolio

Búsqueda avanzada

TIENE EN SU CESTA DE LA COMPRA

0 productos

en total 0,00 €

ACTIVE LEARNING
Título:
ACTIVE LEARNING
Subtítulo:
Autor:
SETTLES, B
Editorial:
MORGAN & CLAYPOOL PUBLISHERS
Año de edición:
2012
Materia
INTELIGENCIA ARTIFICIAL - GENERAL
ISBN:
978-1-60845-725-0
Páginas:
116
31,50 €

 

Sinopsis

The key idea behind active learning is that a machine learning algorithm can perform better with less training if it is allowed to choose the data from which it learns. An active learner may pose ´queries,´ usually in the form of unlabeled data instances to be labeled by an ´oracle´ (e.g., a human annotator) that already understands the nature of the problem. This sort of approach is well-motivated in many modern machine learning and data mining applications, where unlabeled data may be abundant or easy to come by, but training labels are difficult, time-consuming, or expensive to obtain. This book is a general introduction to active learning. It outlines several scenarios in which queries might be formulated, and details many query selection algorithms which have been organized into four broad categories, or ´query selection frameworks.´ We also touch on some of the theoretical foundations of active learning, and conclude with an overview of the strengths and weaknesses of these approaches in practice, including a summary of ongoing work to address these open challenges and opportunities. Table of Contents: Automating Inquiry / Uncertainty Sampling / Searching Through the Hypothesis Space / Minimizing Expected Error and Variance / Exploiting Structure in Data / Theory / Practical Considerations