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ICDM
2010
IEEE
134views Data Mining» more  ICDM 2010»
15 years 5 months ago
Consequences of Variability in Classifier Performance Estimates
The prevailing approach to evaluating classifiers in the machine learning community involves comparing the performance of several algorithms over a series of usually unrelated data...
Troy Raeder, T. Ryan Hoens, Nitesh V. Chawla
AIIA
2005
Springer
16 years 23 days ago
Mining Relational Association Rules for Propositional Classification
In traditional classification setting, training data are represented as a single table, where each row corresponds to an example and each column to a predictor variable or the targ...
Annalisa Appice, Michelangelo Ceci, Donato Malerba
ECAI
2010
Springer
15 years 7 months ago
Mining Outliers with Adaptive Cutoff Update and Space Utilization (RACAS)
Recently the efficiency of an outlier detection algorithm ORCA was improved by RCS (Randomization with faster Cutoff update and Space utilization after pruning), which changes the ...
Chi-Cheong Szeto, Edward Hung
DAWAK
2001
Springer
15 years 11 months ago
A Theoretical Framework for Association Mining Based on the Boolean Retrieval Model
Data mining has been defined as the non- trivial extraction of implicit, previously unknown and potentially useful information from data. Association mining is one of the important...
Peter Bollmann-Sdorra, Aladdin Hafez, Vijay V. Rag...
KDD
2009
ACM
221views Data Mining» more  KDD 2009»
16 years 7 months ago
Migration motif: a spatial - temporal pattern mining approach for financial markets
A recent study by two prominent finance researchers, Fama and French, introduces a new framework for studying risk vs. return: the migration of stocks across size-value portfolio ...
Xiaoxi Du, Ruoming Jin, Liang Ding, Victor E. Lee,...