Extracting both generalized and specialized knowledge by XCS using attribute tracking and feedback
Keiki Takadama, Masaya Nakata · 2015
This paper proposes XCS using Attribute Tracking and Feedback (XCS-ATF) that simultaneously extracts both of the generalized and specialized knowledge, and evaluates its effectiveness by investigating how the extracted knowledge contribute to deriving deep/light sleep of aged persons. The data mining of the daily activities of aged person by XCS-ATF has revealed the following implications: (1) XCS-ATF succeeds to extract the knowledge from the dataset including many contradict data; (2) XCS-ATF can extract not only the generalized knowledge as the daily activities that are usually performed with deriving deep/light sleep but also the specialized knowledge as the daily activities (e.g., birthday party) that are not often performed with deriving deep/light sleep, even though the specialized knowledge which does not often occur tends to be deleted as a noise by the general data mining methods; and (3) XCS-ATF can extract the daily activities that provides nine years younger sleep in the healthy aged persons and seven years younger sleep even in dementia persons who are hard to have a deep sleep in comparison with non-dementia persons.