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GFKL
2005
Springer
133views Data Mining» more  GFKL 2005»
14 years 1 months ago
Finding Persisting States for Knowledge Discovery in Time Series
Abstract. Knowledge Discovery in time series usually requires symbolic time series. Many discretization methods that convert numeric time series to symbolic time series ignore the ...
Fabian Mörchen, Alfred Ultsch
PKDD
2005
Springer
142views Data Mining» more  PKDD 2005»
14 years 1 months ago
Speeding Up Logistic Model Tree Induction
Logistic Model Trees have been shown to be very accurate and compact classifiers [8]. Their greatest disadvantage is the computational complexity of inducing the logistic regressi...
Marc Sumner, Eibe Frank, Mark A. Hall
PKDD
2005
Springer
101views Data Mining» more  PKDD 2005»
14 years 1 months ago
A Random Method for Quantifying Changing Distributions in Data Streams
In applications such as fraud and intrusion detection, it is of great interest to measure the evolving trends in the data. We consider the problem of quantifying changes between tw...
Haixun Wang, Jian Pei
RSFDGRC
2005
Springer
14 years 1 months ago
Intelligent Algorithms for Optical Track Audio Restoration
Abstract. The Unpredictability Measure computation algorithm applied to psychoacoustic model-based broadband noise attenuation is discussed. A learning decision algorithm based on ...
Andrzej Czyzewski, Marek Dziubinski, Lukasz Litwic...
CINQ
2004
Springer
125views Database» more  CINQ 2004»
14 years 1 months ago
The Hows, Whys, and Whens of Constraints in Itemset and Rule Discovery
Many researchers in our community (this author included) regularly emphasize the role constraints play in improving performance of data-mining algorithms. This emphasis has led to ...
Roberto J. Bayardo