Data Mining and Decision Support Integration
published: Feb. 25, 2007, recorded: July 2005, views: 970
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
The aim of this presentation is twofold: (1) to introduce the field of Decision Support (DS), and (2) to provide an overview of possible approaches and benefits of combining DS with Data Mining (DM) in solving real-life decision and data-analysis problems. Related to DS, we define the concepts of decision problem and decision-making, introduce the taxonomy of disciplines related to DS, overview the approach of decision analysis, introduce the method of multi-attribute modeling, and illustrate it through real-life examples of housing loan allocation and risk assessment in medicine. In the main part, we investigate the ways to combine and integrate DS and DM, which generally involve the following categories: (1) DS for DM, (2) DM for DS, (3) DM, then DS, (4) DS, then DM, and (5) DM and DS. Each category is illustrated by a practical example. Two categories are investigated in greater detail. The category “(1) DS for DM” is represented by a method for selecting a best DM-induced classifier based on ROC space exploration. For the category “(5) DM and DS”, we explore an approach of developing qualitative multi-attribute models by combining the systems DEX and HINT. DEX is a DS tool for expert-based (“hand-crafted”) development of models, whereas HINT is a DM tool that develops models from data by a method based on function decomposition.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !