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» Learning from Skewed Class Multi-relational Databases
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ISM
2005
IEEE
138views Multimedia» more  ISM 2005»
14 years 2 months ago
Investigation of Combining SVM and Decision Tree for Emotion Classification
This paper discusses the use of a combination of support vector machine and decision tree learning for recognizing four emotions in speech, which are Neutral, Angry, Lombard, and ...
Thao Nguyen, Mingkun Li, Iris Bass, Ishwar K. Seth...
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
14 years 8 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
14 years 9 months ago
Multi-focal learning and its application to customer service support
In this study, we formalize a multi-focal learning problem, where training data are partitioned into several different focal groups and the prediction model will be learned within...
Yong Ge, Hui Xiong, Wenjun Zhou, Ramendra K. Sahoo...
KDD
2006
ACM
129views Data Mining» more  KDD 2006»
14 years 8 months ago
Suppressing model overfitting in mining concept-drifting data streams
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...
PR
2010
186views more  PR 2010»
13 years 6 months ago
Feature extraction by learning Lorentzian metric tensor and its extensions
We develop a supervised dimensionality reduction method, called Lorentzian Discriminant Projection (LDP), for feature extraction and classification. Our method represents the str...
Risheng Liu, Zhouchen Lin, Zhixun Su, Kewei Tang