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AUSAI
2004
Springer
13 years 11 months ago
Using Classification to Evaluate the Output of Confidence-Based Association Rule Mining
Abstract. Association rule mining is a data mining technique that reveals interesting relationships in a database. Existing approaches employ different parameters to search for int...
Stefan Mutter, Mark Hall, Eibe Frank
ICDM
2010
IEEE
134views Data Mining» more  ICDM 2010»
13 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
JDWM
2007
90views more  JDWM 2007»
13 years 7 months ago
Mining for Mutually Exclusive Items in Transaction Databases
Association rule mining is a popular task that involves the discovery of co-occurences of items in transaction databases. Several extensions of the traditional association rule mi...
George Tzanis, Christos Berberidis
ICDM
2005
IEEE
133views Data Mining» more  ICDM 2005»
14 years 1 months ago
Summarization - Compressing Data into an Informative Representation
In this paper, we formulate the problem of summarization of a dataset of transactions with categorical attributes as an optimization problem involving two objective functions - co...
Varun Chandola, Vipin Kumar
ICDM
2010
IEEE
147views Data Mining» more  ICDM 2010»
13 years 5 months ago
Location and Scatter Matching for Dataset Shift in Text Mining
Dataset shift from the training data in a source domain to the data in a target domain poses a great challenge for many statistical learning methods. Most algorithms can be viewed ...
Bo Chen, Wai Lam, Ivor W. Tsang, Tak-Lam Wong