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» Learning a Classification Model for Segmentation
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166
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EMNLP
2010
15 years 4 months ago
Negative Training Data Can be Harmful to Text Classification
This paper studies the effects of training data on binary text classification and postulates that negative training data is not needed and may even be harmful for the task. Tradit...
Xiaoli Li, Bing Liu, See-Kiong Ng
167
Voted
ICPR
2010
IEEE
15 years 4 months ago
Variational Mixture of Experts for Classification with Applications to Landmine Detection
Abstract--In this paper, we (1) provide a complete framework for classification using Variational Mixture of Experts (VME); (2) derive the variational lower bound; and (3) apply th...
Seniha Esen Yuksel, Paul D. Gader
ICDM
2005
IEEE
163views Data Mining» more  ICDM 2005»
15 years 11 months ago
Efficient Text Classification by Weighted Proximal SVM
In this paper, we present an algorithm that can classify large-scale text data with high classification quality and fast training speed. Our method is based on a novel extension o...
Dong Zhuang, Benyu Zhang, Qiang Yang, Jun Yan, Zhe...
195
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CIKM
2008
Springer
15 years 8 months ago
Structure feature selection for graph classification
With the development of highly efficient graph data collection technology in many application fields, classification of graph data emerges as an important topic in the data mining...
Hongliang Fei, Jun Huan
160
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IJAR
2008
93views more  IJAR 2008»
15 years 6 months ago
Prototype based fuzzy classification in clinical proteomics
Proteomic profiling based on mass spectrometry is an important tool for studies at the protein and peptide level in medicine and health care. Thereby, the identification of releva...
Frank-Michael Schleif, Thomas Villmann, Barbara Ha...