Essential Mining Approaches to Problem Solving

Essential Mining Approaches to Problem Solving

Stephan Kudyba (Economic Consultant, USA) and Richard Hoptroff (Consultant, The Netherlands)
Copyright: © 2001 |Pages: 11
DOI: 10.4018/978-1-930708-03-7.ch004
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Abstract

Forecasting and “what if” mining generally incorporates the application of regression and neural network methodologies. In certain cases, for more simple applications, univariate forecasting methods can be used. Forecasting procedures are more affiliated with time series data or historic data that extend back in time (e.g., monthly periods over several years). Other mining applications involve examining a section of data over a specified time period, (e.g., looking at a number of customers, employees or processes over a given time period, let’s say a six-month period). This approach is referred to as a cross-sectional analysis mentioned briefly in the last chapter. The following section will describe these mining approaches in a bit more detail to give you an idea of not only how to effectively implement them, but also when and in what situation you may need to apply them.

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