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» Mining Prediction Rules from Minority Classes
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KES
2004
Springer
15 years 2 months ago
A Comparison of Two Approaches to Data Mining from Imbalanced Data
Our objective is a comparison of two data mining approaches to dealing with imbalanced data sets. The first approach is based on saving the original rule set, induced by the LEM2 ...
Jerzy W. Grzymala-Busse, Jerzy Stefanowski, Szymon...
98
Voted
ISDA
2010
IEEE
14 years 7 months ago
Comparing SVM ensembles for imbalanced datasets
Real life datasets often suffer from the problem of class imbalance, which thwarts supervised learning process. In such data sets examples of positive (minority) class are signific...
Vasudha Bhatnagar, Manju Bhardwaj, Ashish Mahabal
64
Voted
AUSDM
2006
Springer
82views Data Mining» more  AUSDM 2006»
15 years 1 months ago
Generality Is Predictive of Prediction Accuracy
During knowledge acquisition multiple alternative potential rules all appear equally credible. This paper addresses the dearth of formal analysis about how to select between such a...
Geoffrey I. Webb, Damien Brain
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
15 years 10 months ago
Practical learning from one-sided feedback
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...
D. Sculley
ACIIDS
2009
IEEE
162views Database» more  ACIIDS 2009»
15 years 2 months ago
Deriving Conceptual Schema from XML Databases
In this paper, two concepts from different research areas are addressed together, namely functional dependency (FD) and multidimensional association rule (MAR). FD is a class of i...
Oviliani Yenty Yuliana, Suphamit Chittayasothorn