Exceptional Model Mining
published: July 5, 2008, recorded: June 2008, views: 146
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.
In most databases, it is possible to identify small partitions of the data where the observeddistribution is notably different from that of the database as a whole. In classical subgroup discovery, one considers the distribution of a single nominal attribute, and exceptional subgroups show a surprising increase in the occurrence of one of its values. In this talk, I'll introduce Exceptional Model Mining (EMM), a framework that allows for more complicated target concepts. Rather than finding subgroups based on the distribution of a single target attribute, EMM finds subgroups where a model fitted to that subgroup is somehow exceptional. I'll discuss regression as well as classification models, and define quality measures that determine how exceptional a given model on a subgroup is. Our framework is general enough to be applied to many types of models, even from other paradigms such as association analysis and graphical modeling.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !