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» Sensing-aware classification with high-dimensional data
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CATA
2004
13 years 6 months ago
Decision Tree Induction for Dynamic, High-Dimensional Data Using P-Trees
1 Decision Tree Induction is a powerful classification tool that is much used in practice and works well for static data with dozens of attributes. We adapt the decision tree conce...
Anne Denton, William Perrizo
JMLR
2010
101views more  JMLR 2010»
12 years 11 months ago
Exploiting Feature Covariance in High-Dimensional Online Learning
Some online algorithms for linear classification model the uncertainty in their weights over the course of learning. Modeling the full covariance structure of the weights can prov...
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer...
PAKDD
2005
ACM
133views Data Mining» more  PAKDD 2005»
13 years 10 months ago
Feature Selection for High Dimensional Face Image Using Self-organizing Maps
: While feature selection is very difficult for high dimensional, unstructured data such as face image, it may be much easier to do if the data can be faithfully transformed into l...
Xiaoyang Tan, Songcan Chen, Zhi-Hua Zhou, Fuyan Zh...
ICPR
2006
IEEE
14 years 5 months ago
Finding Rule Groups to Classify High Dimensional Gene Expression Datasets
Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attrac...
Jiyuan An, Yi-Ping Phoebe Chen
WWW
2009
ACM
14 years 5 months ago
Latent space domain transfer between high dimensional overlapping distributions
Transferring knowledge from one domain to another is challenging due to a number of reasons. Since both conditional and marginal distribution of the training data and test data ar...
Sihong Xie, Wei Fan, Jing Peng, Olivier Verscheure...