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BMCBI
2010
153views more  BMCBI 2010»
15 years 6 months ago
Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering
Background: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
Eva Freyhult, Mattias Landfors, Jenny Önskog,...
GLVLSI
2007
IEEE
158views VLSI» more  GLVLSI 2007»
15 years 8 months ago
RT-level vector selection for realistic peak power simulation
We present a vector selection methodology for estimating the peak power dissipation in a CMOS logic circuit. The ultimate goal is to combine the speed of RT-level simulation with ...
Chia-Chien Weng, Ching-Shang Yang, Shi-Yu Huang
BMCBI
2006
146views more  BMCBI 2006»
15 years 6 months ago
Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE
Background: In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease...
Satoshi Niijima, Satoru Kuhara
JMLR
2008
100views more  JMLR 2008»
15 years 6 months ago
Hit Miss Networks with Applications to Instance Selection
In supervised learning, a training set consisting of labeled instances is used by a learning algorithm for generating a model (classifier) that is subsequently employed for decidi...
Elena Marchiori
ICCV
2009
IEEE
16 years 11 months ago
Efficient subset selection based on the Renyi entropy
Many machine learning algorithms require the summation of Gaussian kernel functions, an expensive operation if implemented straightforwardly. Several methods have been proposed t...
Vlad I. Morariu1, Balaji V. Srinivasan, Vikas C. R...