Name: Proactive Data Mining With Decision Trees (Springerbriefs in Electrical and Computer Engineering) (en Inglés)
SKU: 50875424
Price: 59.05 USD
Availability: InStock
Author: Haim Dahan; Shahar Cohen; Lior Rokach; Oded Maimon
ISBN: 9781493905386

portada Proactive Data Mining With Decision Trees (Springerbriefs in Electrical and Computer Engineering) (en Inglés)

Proactive Data Mining With Decision Trees (Springerbriefs in Electrical and Computer Engineering) (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Haim Dahan; Shahar Cohen; Lior Rokach; Oded Maimon

Año

2014

Idioma

Inglés

N° páginas

100

Encuadernación

Tapa Blanda

ISBN13

9781493905386

N° edición

2014

Categorías

Minería de datos («data mining»)

Proactive Data Mining With Decision Trees (Springerbriefs in Electrical and Computer Engineering) (en Inglés)

Haim Dahan; Shahar Cohen; Lior Rokach; Oded Maimon (Autor) · Springer · Tapa Blanda

Libro Nuevo Importado

Envío: 20 a 27 días háb.

$ 107.37$ 59.05

-45%

Costos de importación incluídos en el precio ✅

Libro Nuevo

Quedan más de 100 unidades

$ 59.05

Llega entre el 20 Oct y el 04 Nov a Quito, Pichincha. Seleccionar ubicación

Agregar a lista de deseos

Reseña del libro "Proactive Data Mining With Decision Trees (Springerbriefs in Electrical and Computer Engineering) (en Inglés)"

This book explores a proactive and domain-driven method to classification tasks. This novel proactive approach to data mining not only induces a model for predicting or explaining a phenomenon, but also utilizes specific problem/domain knowledge to suggest specific actions to achieve optimal changes in the value of the target attribute. In particular, the authors suggest a specific implementation of the domain-driven proactive approach for classification trees. The book centers on the core idea of moving observations from one branch of the tree to another. It introduces a novel splitting criterion for decision trees, termed maximal-utility, which maximizes the potential for enhancing profitability in the output tree. Two real-world case studies, one of a leading wireless operator and the other of a major security company, are also included and demonstrate how applying the proactive approach to classification tasks can solve business problems. Proactive Data Mining with Decision Trees is intended for researchers, practitioners and advanced-level students.