Predictive Data Mining Models

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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