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» Using Anonymized Data for Classification
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CATA
2009
15 years 3 months ago
Nearest Shrunken Centroid as Feature Selection of Microarray Data
The nearest shrunken centroid classifier uses shrunken centroids as prototypes for each class and test samples are classified to belong to the class whose shrunken centroid is nea...
Myungsook Klassen, Nyunsu Kim
CONEXT
2008
ACM
15 years 4 months ago
Internet traffic classification demystified: myths, caveats, and the best practices
Recent research on Internet traffic classification algorithms has yielded a flurry of proposed approaches for distinguishing types of traffic, but no systematic comparison of the ...
Hyunchul Kim, Kimberly C. Claffy, Marina Fomenkov,...
ECOI
2010
117views more  ECOI 2010»
15 years 2 months ago
Ensemble extraction for classification and detection of bird species
Advances in technology have enabled new approaches for sensing the environment and collecting data about the world. Once collected, sensor readings can be assembled into data stre...
Eric P. Kasten, Philip K. McKinley, Stuart H. Gage
166
Voted
FLAIRS
2007
15 years 4 months ago
Enhancing the Performance of Semi-Supervised Classification Algorithms with Bridging
Traditional supervised classification algorithms require a large number of labelled examples to perform accurately. Semi-supervised classification algorithms attempt to overcome t...
Jason Chan, Josiah Poon, Irena Koprinska
BMCBI
2010
135views more  BMCBI 2010»
15 years 2 months ago
Simple and flexible classification of gene expression microarrays via Swirls and Ripples
Background: A simple classification rule with few genes and parameters is desirable when applying a classification rule to new data. One popular simple classification rule, diagon...
Stuart G. Baker