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» A supervised learning approach for imbalanced data sets
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ICDM
2006
IEEE
158views Data Mining» more  ICDM 2006»
14 years 4 months ago
Detection of Interdomain Routing Anomalies Based on Higher-Order Path Analysis
Internet routing dynamics have been extensively studied in the past few years. However, dynamics such as interdomain Border Gateway Protocol (BGP) behavior are still poorly unders...
Murat Can Ganiz, Sudhan Kanitkar, Mooi Choo Chuah,...
PRIB
2009
Springer
209views Bioinformatics» more  PRIB 2009»
14 years 4 months ago
Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm
For many biomedical modelling tasks a number of different types of data may influence predictions made by the model. An established approach to pursuing supervised learning with ...
Yiming Ying, Colin Campbell, Theodoros Damoulas, M...
JAIR
2002
95views more  JAIR 2002»
13 years 10 months ago
SMOTE: Synthetic Minority Over-sampling Technique
An approach to the construction of classifiers from imbalanced datasets is described. A dataset is imbalanced if the classification categories are not approximately equally repres...
Nitesh V. Chawla, Kevin W. Bowyer, Lawrence O. Hal...
ICTAI
2006
IEEE
14 years 4 months ago
Learning to Predict Salient Regions from Disjoint and Skewed Training Sets
We present an ensemble learning approach that achieves accurate predictions from arbitrarily partitioned data. The partitions come from the distributed processing requirements of ...
Larry Shoemaker, Robert E. Banfield, Lawrence O. H...
SIGIR
2008
ACM
13 years 10 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff