DocumentCode :
2384028
Title :
Inductive inference of model structure using hypothesis feedback
Author :
Birdwell, J.D. ; Cockett, J.R.B.
Author_Institution :
Dept. of Electr. & Comput. Eng., Tennessee Univ., Knoxville, TN, USA
fYear :
1988
fDate :
7-9 June 1988
Firstpage :
1891
Abstract :
The authors describe initial results in the application of methods based on discrete decision theory to the inductive inference of models from collected data. The results are applied to the classification of electric distribution system customers for direct load control. These preliminary results are intended as an exploratory attempt to use discrete decision theory for inference of the structure of large collections of data. The analysis of collected data is modeled as a set of operations which induce equivalence relations on the data and generate meaningful figures of merit for the resulting equivalence classes. The effect is to reduce the data analysis problem to the detection of structure in the figure of merit functions over the set of equivalence classes. An inference algorithm is used to detect this structure and classify the customers into load types.<>
Keywords :
data analysis; decision theory; distribution networks; inference mechanisms; knowledge acquisition; load regulation; customers classification; data analysis; decision trees; discrete decision theory; electric distribution system; hypothesis feedback; inductive inference; model structure; Application software; Chemical analysis; Chemical processes; Data analysis; Data engineering; Databases; Decision theory; Feedback; Inference algorithms; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1988., IEEE International Symposium on
Conference_Location :
Espoo, Finland
Type :
conf
DOI :
10.1109/ISCAS.1988.15306
Filename :
15306
Link To Document :
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