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» Discovering decision rules from numerical data streams
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EPIA
2003
Springer
13 years 11 months ago
Mining Low Dimensionality Data Streams of Continuous Attributes
This paper presents an incremental and scalable learning algorithm in order to mine numeric, low dimensionality, high–cardinality, time–changing data streams. Within the Superv...
Francisco J. Ferrer-Troyano, Jesús S. Aguil...
DATAMINE
1998
106views more  DATAMINE 1998»
13 years 5 months ago
Discovering Robust Knowledge from Databases that Change
Many applications of knowledge discovery and data mining such as rule discovery for semantic query optimization, database integration and decision support, require the knowledge t...
Chun-Nan Hsu, Craig A. Knoblock
DAWAK
2008
Springer
13 years 7 months ago
Mining Serial Episode Rules with Time Lags over Multiple Data Streams
The problem of discovering episode rules from static databases has been studied for years due to its wide applications in prediction. In this paper, we make the first attempt to st...
Tung-Ying Lee, En Tzu Wang, Arbee L. P. Chen
GRC
2010
IEEE
13 years 7 months ago
Local Pattern Mining from Sequences Using Rough Set Theory
Abstract--Sequential pattern mining is a crucial but challenging task in many applications, e.g., analyzing the behaviors of data in transactions and discovering frequent patterns ...
Ken Kaneiwa, Yasuo Kudo
IDA
2008
Springer
13 years 6 months ago
Symbolic methodology for numeric data mining
Currently statistical and artificial neural network methods dominate in data mining applications. Alternative relational (symbolic) data mining methods have shown their effectivene...
Boris Kovalerchuk, Evgenii Vityaev