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» Data Mining Methodological Weaknesses and Suggested Fixes
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AUSDM
2006
Springer
100views Data Mining» more  AUSDM 2006»
13 years 9 months ago
Data Mining Methodological Weaknesses and Suggested Fixes
Predictive accuracy claims should give explicit descriptions of the steps followed, with access to the code used. This allows referees and readers to check for common traps, and t...
John H. Maindonald
ICDE
2008
IEEE
195views Database» more  ICDE 2008»
14 years 7 months ago
LOCUST: An Online Analytical Processing Framework for High Dimensional Classification of Data Streams
Abstract-- In recent years, data streams have become ubiquitous because of advances in hardware and software technology. The ability to adapt conventional mining problems to data s...
Charu C. Aggarwal, Philip S. Yu
AUSDM
2008
Springer
227views Data Mining» more  AUSDM 2008»
13 years 7 months ago
Exploratory Mining over Organisational Communications Data
Exploratory data mining is fundamental to fostering an appreciation of complex datasets. For large and continuously growing datasets, such as obtained by regular sampling of an or...
Alan Allwright, John F. Roddick
DMIN
2009
142views Data Mining» more  DMIN 2009»
13 years 3 months ago
Action Selection in Customer Value Optimization: An Approach Based on Covariate-Dependent Markov Decision Processes
Typical methods in CRM marketing include action selection on the basis of Markov Decision Processes with fixed transition probabilities on the one hand, and scoring customers separ...
Angi Roesch, Harald Schmidbauer
ICDM
2002
IEEE
188views Data Mining» more  ICDM 2002»
13 years 10 months ago
A Comparative Study of RNN for Outlier Detection in Data Mining
We have proposed replicator neural networks (RNNs) as an outlier detecting algorithm [15]. Here we compare RNN for outlier detection with three other methods using both publicly a...
Graham J. Williams, Rohan A. Baxter, Hongxing He, ...