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AI
2001
Springer
14 years 10 days ago
A Case Study for Learning from Imbalanced Data Sets
We present our experience in applying a rule induction technique to an extremely imbalanced pharmaceutical data set. We focus on using a variety of performance measures to evaluate...
Aijun An, Nick Cercone, Xiangji Huang
KDD
2005
ACM
139views Data Mining» more  KDD 2005»
14 years 1 months ago
Learning to predict train wheel failures
This paper describes a successful but challenging application of data mining in the railway industry. The objective is to optimize maintenance and operation of trains through prog...
Chunsheng Yang, Sylvain Létourneau
PROMISE
2010
13 years 2 months ago
On the value of learning from defect dense components for software defect prediction
BACKGROUND: Defect predictors learned from static code measures can isolate code modules with a higher than usual probability of defects. AIMS: To improve those learners by focusi...
Hongyu Zhang, Adam Nelson, Tim Menzies
ICTAI
2006
IEEE
14 years 1 months ago
Learning to Predict Salient Regions from Disjoint and Skewed Training Sets
We present an ensemble learning approach that achieves accurate predictions from arbitrarily partitioned data. The partitions come from the distributed processing requirements of ...
Larry Shoemaker, Robert E. Banfield, Lawrence O. H...