发帖
雷达卡
Authors: David L. Olson, Desheng Wu
Includes detailed discussions of time series data and different characteristics that data may have
Describes data mining processes used in predictive modeling
Includes demonstrations of modeling with R and with Matlab
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.
Table of contents
Front Matter
Knowledge Management
Data Sets
Basic Forecasting Tools
Multiple Regression
Regression Tree Models
Autoregressive Models
Classification Tools
Predictive Models and Big Data
Back Matter
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