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MLDM
2007
Springer
14 years 3 months ago
Nonlinear Feature Selection by Relevance Feature Vector Machine
Support vector machine (SVM) has received much attention in feature selection recently because of its ability to incorporate kernels to discover nonlinear dependencies between feat...
Haibin Cheng, Haifeng Chen, Guofei Jiang, Kenji Yo...
ISNN
2011
Springer
13 years 18 days ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
ICDM
2010
IEEE
185views Data Mining» more  ICDM 2010»
13 years 7 months ago
Detecting Non-compliant Consumers in Spatio-Temporal Health Data: A Case Study from Medicare Australia
This paper describes our experience with applying data mining techniques to the problem of fraud detection in spatio-temporal health data in Medicare Australia. A modular framework...
Kee Siong Ng, Yin Shan, D. Wayne Murray, Alison Su...
EMNLP
2009
13 years 7 months ago
Improving Dependency Parsing with Subtrees from Auto-Parsed Data
This paper presents a simple and effective approach to improve dependency parsing by using subtrees from auto-parsed data. First, we use a baseline parser to parse large-scale una...
Wenliang Chen, Jun'ichi Kazama, Kiyotaka Uchimoto,...
IJCNN
2006
IEEE
14 years 3 months ago
Tentacled Self-Organizing Map for Effective Data Extraction
— Since we can accumulate a huge amount of data including useless information in these years, it is important to investigate various extraction method of clusters from data inclu...
Haruna Matsushita, Yoshifumi Nishio