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FLAIRS
2008
15 years 6 months ago
Selecting Minority Examples from Misclassified Data for Over-Sampling
We introduce a method to deal with the problem of learning from imbalanced data sets, where examples of one class significantly outnumber examples of other classes. Our method sel...
Jorge de la Calleja, Olac Fuentes, Jesús Go...
FLAIRS
2004
15 years 6 months ago
Semi-Supervised Sequence Classification with HMMs
Using unlabeled data to help supervised learning has become an increasingly attractive methodology and proven to be effective in many applications. This paper applies semi-supervi...
Shi Zhong
141
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DATAMINE
2006
139views more  DATAMINE 2006»
15 years 4 months ago
Discovering Classification from Data of Multiple Sources
In many large e-commerce organizations, multiple data sources are often used to describe the same customers, thus it is important to consolidate data of multiple sources for intell...
Charles X. Ling, Qiang Yang
ECML
2004
Springer
15 years 10 months ago
Batch Reinforcement Learning with State Importance
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Lihong Li, Vadim Bulitko, Russell Greiner
ICALT
2006
IEEE
15 years 10 months ago
Adaptive Learning Objects Sequencing for Competence-Based Learning
Lifelong learning refers to the activities people perform throughout their life to improve their competence in a particular field. Although adaptive educational hypermedia systems...
Pythagoras Karampiperis, Demetrios G. Sampson