TY - JOUR
T1 - Functional behavioral assessment using the LERS data mining system - Strategies for understanding complex physiological and behavioral patterns
AU - Freeman, Rachel L.
AU - Grzymala-Busse, Jerzy W.
AU - Harvey, Mark
PY - 2003/9
Y1 - 2003/9
N2 - Many individuals with mental retardation, autism, and other related disabilities lead lives that are significantly restricted because of problem behaviors such as self-injury and aggression. We processed two data sets, one describing heart rate patterns and the other describing the behavioral events of one subject diagnosed with severe mental retardation, visual impairments, and severe problem behavior. From these data sets the LERS data mining system induced certain and possible rule sets. In our research these rule sets were successfully used for interpretation, or, more specifically, to discover mechanisms of triggering specific physiological and behavioral patterns.
AB - Many individuals with mental retardation, autism, and other related disabilities lead lives that are significantly restricted because of problem behaviors such as self-injury and aggression. We processed two data sets, one describing heart rate patterns and the other describing the behavioral events of one subject diagnosed with severe mental retardation, visual impairments, and severe problem behavior. From these data sets the LERS data mining system induced certain and possible rule sets. In our research these rule sets were successfully used for interpretation, or, more specifically, to discover mechanisms of triggering specific physiological and behavioral patterns.
KW - Data mining
KW - LEM2 algorithm
KW - LERS
KW - Self-injurious behavior
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U2 - 10.1023/A:1024762516786
DO - 10.1023/A:1024762516786
M3 - Article
AN - SCOPUS:0042429196
SN - 0925-9902
VL - 21
SP - 173
EP - 181
JO - Journal of Intelligent Information Systems
JF - Journal of Intelligent Information Systems
IS - 2
ER -