CIKM
2011
Springer
13 years 11 days ago
2011
Springer
Various semi-supervised learning methods have been proposed recently to solve the long-standing shortage problem of manually labeled data in sentiment classification. However, mos...
ICCV
2011
IEEE
13 years 13 days ago
2011
IEEE
We present an approach for dictionary learning of action attributes via information maximization. We unify the class distribution and appearance information into an objective func...
CORR
2011
Springer
13 years 4 months ago
2011
Springer
For large, real-world inductive learning problems, the number of training examples often must be limited due to the costs associated with procuring, preparing, and storing the tra...
LREC
2008
14 years 1 months ago
2008
One problem of data-driven answer extraction in open-domain factoid question answering is that the class distribution of labeled training data is fairly imbalanced. This imbalance...
IFIP12
2008
14 years 1 months ago
2008
Sampling methods are a direct approach to tackle the problem of class imbalance. These methods sample a data set in order to alter the class distributions. Usually these methods ar...
WSOM
2009
Springer
14 years 5 months ago
2009
Springer
Abstract. The distribution of a class of objects, such as images depicting a specific topic, can be studied by observing the best-matching units (BMUs) of the objects’ feature v...
AI
2009
Springer
14 years 7 months ago
2009
Springer
In many practical domains, misclassification costs can differ greatly and may be represented by class ratios, however, most learning algorithms struggle with skewed class distrib...
KDD
2009
ACM
2009
ACM
Quantification and semi-supervised classification methods for handling changes in class distribution
15 years 29 days ago
In realistic settings the prevalence of a class may change after a classifier is induced and this will degrade the performance of the classifier. Further complicating this scenari...