Name: Metalearning: Applications to Automated Machine Learning and Data Mining (en Inglés)
Price: 1400.18 MXN
Availability: InStock
Author: Brazdil, Pavel ; Van Rijn, Jan N. ; Soares, Carlos
ISBN: 9783030670238

Envío gratis

portada Metalearning: Applications to Automated Machine Learning and Data Mining (en Inglés)

Formato

Libro Físico

Autor

Editorial

Idioma

Inglés

N° páginas

346

Encuadernación

Tapa Dura

Dimensiones

23.4 x 15.6 x 2.1 cm

Peso

0.68 kg.

ISBN13

9783030670238

N° edición

0002

Categorías

Probabilidad y estadística
Data mining: minería de datos
Inteligencia artificial

Metalearning: Applications to Automated Machine Learning and Data Mining (en Inglés)

Carlos Soares (Autor) · Pavel Brazdil (Autor) · Jan N. Van Rijn (Autor) · Springer · Tapa Dura

Libro Nuevo

$ 1,400.18

$ 2,545.78

Ahorras: $ 1,145.60

45% descuento

Envío normal

Origen: Estados Unidos (Costos de importación incluídos en el precio)

Se enviará desde nuestra bodega entre el Lunes 12 de Agosto y el Viernes 23 de Agosto.

Lo recibirás en cualquier lugar de México entre 1 y 3 días hábiles luego del envío.

Reseña del libro "Metalearning: Applications to Automated Machine Learning and Data Mining (en Inglés)"

Metalearning is the study of principled methods that exploit metaknowledge to obtain efficient models and solutions by adapting machine learning and data mining processes. While the variety of machine learning and data mining techniques now available can, in principle, provide good model solutions, a methodology is still needed to guide the search for the most appropriate model in an efficient way. Metalearning provides one such methodology that allows systems to become more effective through experience. This book discusses several approaches to obtaining knowledge concerning the performance of machine learning and data mining algorithms. It shows how this knowledge can be reused to select, combine, compose and adapt both algorithms and models to yield faster, more effective solutions to data mining problems. It can thus help developers improve their algorithms and also develop learning systems that can improve themselves. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining and artificial intelligence.