DocumentCode
443970
Title
Self-reproducing learning, data mining and intelligent predictive systems
Author
Huang, James Kuodo
Author_Institution
California Inst. of Technol., Alhambra, CA, USA
Volume
1
fYear
2005
fDate
25-27 July 2005
Firstpage
159
Abstract
Self-reproducing learning mechanism is a type of learning technique which was developed from our intelligent predictive systems. It is very useful to be applied to our Lotto Predictive System to increase the performance of prediction. Self-reproducing learning technique is part of our knowledge discovery data mining tools on Lotto predictive system. Lotto predictive system is also based on human super nature beliefs as part of its knowledge. A generalized "pick n out of m" Lotto problem drawn daily for any fixed integer n and m where 8n≥m≥17 has been studied and used to describe self-reproducing learning systems and intelligent predictive systems.
Keywords
data mining; unsupervised learning; Lotto intelligent predictive system; data mining; human super nature beliefs; knowledge discovery; self-reproducing learning; Artificial intelligence; Computer science; Data mining; Deductive databases; Educational institutions; Humans; Intelligent systems; Knowledge engineering; Learning systems; TV; Artificial Intelligence; Database; Knowledge Engineering; Learning Systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing, 2005 IEEE International Conference on
Print_ISBN
0-7803-9017-2
Type
conf
DOI
10.1109/GRC.2005.1547257
Filename
1547257
Link To Document