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ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
13 years 9 months ago
Multi-label Feature Selection for Graph Classification
Nowadays, the classification of graph data has become an important and active research topic in the last decade, which has a wide variety of real world applications, e.g. drug acti...
Xiangnan Kong, Philip S. Yu
ICDM
2010
IEEE
108views Data Mining» more  ICDM 2010»
13 years 9 months ago
Assessing Data Mining Results on Matrices with Randomization
Abstract--Randomization is a general technique for evaluating the significance of data analysis results. In randomizationbased significance testing, a result is considered to be in...
Markus Ojala
ICDM
2010
IEEE
152views Data Mining» more  ICDM 2010»
13 years 9 months ago
Reviewer Profiling Using Sparse Matrix Regression
Thousands of scientific conferences happen every year, and each involves a laborious scientific peer review process conducted by one or more busy scientists serving as Technical/Sc...
Evangelos E. Papalexakis, Nicholas D. Sidiropoulos...
ICIP
2010
IEEE
13 years 9 months ago
Building Emerging Pattern (EP) Random forest for recognition
The Random forest classifier comes to be the working horse for visual recognition community. It predicts the class label of an input data by aggregating the votes of multiple tree...
Liang Wang, Yizhou Wang, Debin Zhao
ICMLC
2010
Springer
13 years 9 months ago
A comparative study on two large-scale hierarchical text classification tasks' solutions
: Patent classification is a large scale hierarchical text classification (LSHTC) task. Though comprehensive comparisons, either learning algorithms or feature selection strategies...
Jian Zhang, Hai Zhao, Bao-Liang Lu
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