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» Predicting relative performance of classifiers from samples
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IWANN
2005
Springer
14 years 2 months ago
Balanced Boosting with Parallel Perceptrons
Boosting constructs a weighted classifier out of possibly weak learners by successively concentrating on those patterns harder to classify. While giving excellent results in many ...
Iván Cantador, José R. Dorronsoro
IGARSS
2009
13 years 6 months ago
Active Learning of Hyperspectral Data with Spatially Dependent Label Acquisition Costs
Supervised learners can be used to automatically classify many types of spatially distributed data. For example, land cover classification by hyperspectral image data analysis is ...
Alexander Liu, Goo Jun, Joydeep Ghosh
IPSN
2004
Springer
14 years 2 months ago
Rate-distortion problem for physics based distributed sensing
We consider the rate-distortion problem for sensing the continuous space-time physical temperature in a circular ring on which a heat source is applied over space and time, and wh...
Baltasar Beferull-Lozano, Robert L. Konsbruck, Mar...
APWEB
2009
Springer
14 years 1 months ago
Ontology Evaluation through Text Classification
We present a new method to evaluate a search ontology, which relies on mapping ontology instances to textual documents. On the basis of this mapping, we evaluate the adequacy of on...
Yael Dahan Netzer, David Gabay, Meni Adler, Yoav G...
BMCBI
2004
205views more  BMCBI 2004»
13 years 8 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma