Predictive Data Mining Models

This book reviews forecasting data mining models, from basic tools for stable data through causal models, to more advanced models using trends and cycles. These models are demonstrated on the basis of business-related data, including stock indices, crude oil prices, and the price of gold. The book's main approach is above all descriptive, seeking to explain how the methods concretely work; as such, it includes selected citations, but does not go into deep scholarly reference. The data sets and software reviewed were selected for their widespread availability to all readers with internet access.

Sommario

Chapter 1 Knowledge Management.- Chapter 2 Data Sets.- Chapter 3 Basic Forecasting ToolsChapter 3 Basic Forecasting Tools.- Chapter 4 Multiple Regression.- Chapter 5 Regression Tree Models.- Chapter 6 Autoregressive Models.- Chapter 7 GARCH Models.- Chapter 8 Comparison of Models.

Dettagli sul prodotto

• Autori: David L. Olson, Desheng Wu
• Editore: Springer, Berlin
• Lingue: Inglese
• Formato: Copertina rigida
• Pubblicazione: 01.01.2016
• EAN: 9789811025426
• ISBN: 978-981-10-2542-6
• Pagine: 102
• Dimensioni: 167 mm x 242 mm x 12 mm
• Peso: 307 g
• Illustrazioni: 6 SW-Abb., 48 Farbabb., 105 Farbtabellen
• Serie: Computational Risk Management
• Categoria: Scienze sociali, diritto, economia > Economia > Management