Title
Combined effects of class imbalance and class overlap on instance-based classification
Abstract
In real-world applications, it has been often observed that class imbalance (significant differences in class prior probabilities) may produce an important deterioration of the classifier performance, in particular with patterns belonging to the less represented classes. This effect becomes especially significant on instance-based learning due to the use of some dissimilarity measure. We analyze the effects of class imbalance on the classifier performance and how the overlap has influence on such an effect, as well as on several techniques proposed in the literature to tackle the class imbalance. Besides, we study how these methods affect to the performance on both classes, not only on the minority class as usual.
Year
DOI
Venue
2006
10.1007/11875581_45
IDEAL
Keywords
Field
DocType
instance-based classification,significant difference,minority class,class prior probability,important deterioration,dissimilarity measure,real-world application,classifier performance,class imbalance,combined effect,instance based learning
Weighted distance,Pattern recognition,Computer science,Artificial intelligence,Classifier (linguistics),Prior probability,Machine learning
Conference
Volume
ISSN
ISBN
4224
0302-9743
3-540-45485-3
Citations 
PageRank 
References 
5
0.51
13
Authors
5
Name
Order
Citations
PageRank
V. García12268.34
R. Alejo215810.40
José Salvador Sánchez356531.62
J. M. Sotoca41094.59
Ramón A. Mollineda538320.41