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KDD
2004
ACM
139views Data Mining» more  KDD 2004»
16 years 4 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
IEAAIE
2010
Springer
15 years 1 months ago
The Combination of a Causal and Emotional Learning Mechanism for an Improved Cognitive Tutoring Agent
This paper describes a Conscious Tutoring System (CTS) capable of dynamic fine-tuned assistance to users. We put forth the combination of a Causal Learning and Emotional learning m...
Usef Faghihi, Philippe Fournier-Viger, Roger Nkamb...
PAKDD
2009
ACM
263views Data Mining» more  PAKDD 2009»
15 years 10 months ago
Spatial Weighting for Bag-of-Visual-Words and Its Application in Content-Based Image Retrieval
It is a challenging and important task to retrieve images from a large and highly varied image data set based on their visual contents. Problems like how to fill the semantic gap b...
Xin Chen, Xiaohua Hu, Xiajiong Shen
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
16 years 4 months ago
A highly-usable projected clustering algorithm for gene expression profiles
Projected clustering has become a hot research topic due to its ability to cluster high-dimensional data. However, most existing projected clustering algorithms depend on some cri...
Kevin Y. Yip, David W. Cheung, Michael K. Ng
ICDM
2008
IEEE
145views Data Mining» more  ICDM 2008»
15 years 10 months ago
Paired Learners for Concept Drift
To cope with concept drift, we paired a stable online learner with a reactive one. A stable learner predicts based on all of its experience, whereas a reactive learner predicts ba...
Stephen H. Bach, Marcus A. Maloof