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AI
2001
Springer
15 years 11 months 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
FLAIRS
2007
15 years 8 months ago
A Distance-Based Over-Sampling Method for Learning from Imbalanced Data Sets
Many real-world domains present the problem of imbalanced data sets, where examples of one classes significantly outnumber examples of other classes. This makes learning difficu...
Jorge de la Calleja, Olac Fuentes
LREC
2008
105views Education» more  LREC 2008»
15 years 7 months ago
Extraction and Evaluation of Keywords from Learning Objects: a Multilingual Approach
We report about a project which brings together Natural Language Processing and eLearning. One of the functionalities developed within this project is the possibility to annotate ...
Lothar Lemnitzer, Paola Monachesi
PRL
2008
91views more  PRL 2008»
15 years 6 months ago
Fuzzy relevance vector machine for learning from unbalanced data and noise
Handing unbalanced data and noise are two important issues in the field of machine learning. This paper proposed a complete framework of fuzzy relevance vector machine by weightin...
Dingfang Li, Wenchao Hu, Wei Xiong, Jin-Bo Yang
CIARP
2009
Springer
16 years 1 months ago
Learning Relational Grammars from Sequences of Actions
Many tasks can be described by sequences of actions that normally exhibit some form of structure and that can be represented by a grammar. This paper introduces FOSeq, an algorithm...
Blanca Vargas-Govea, Eduardo F. Morales