Contacto
Cómo comprar
Entrega
Guía de compras
Latent Factor Analysis for High-dimensional and Sparse Matrices
A particle swarm optimization-based approach
Inglés
125 b
Hasta 30 días para devoluciones
Clientes que también han comprado
/
Tapa blanda
43.59
€
Latent factor analysis models are an effective type of machine learning model for addressing high-dimensional and sparse matrices, which are encountered in many big-data-related industrial applications. The performance of a latent factor analysis model relies heavily on appropriate hyper-parameters. However, most hyper-parameters are data-dependent, and using grid-search to tune these hyper-parameters is truly laborious and expensive in computational terms. Hence, how to achieve efficient hyper-parameter adaptation for latent factor analysis models has become a significant question.This is the first book to focus on how particle swarm optimization can be incorporated into latent factor analysis for efficient hyper-parameter adaptation, an approach that offers high scalability in real-world industrial applications.The book will help students, researchers and engineers fully understand the basic methodologies of hyper-parameter adaptation via particle swarm optimization in latent factor analysis models. Further, it will enable them to conduct extensive research and experiments on the real-world applications of the content discussed.
Sobre el libro
Inglés
Categorías
Regale este libro hoy
Es fácil
1 Añadir al carrito y elegir Entregar como regalo en el checkout 2 Le enviaremos un vale 3 El libro llegará a la dirección del destinatarioTambién puede interesarle
/
Tapa dura
53.39
€
/
Tapa blanda
15.89
€
