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NN
2010
Springer
183views Neural Networks» more  NN 2010»
13 years 7 months ago
Dimensionality reduction for density ratio estimation in high-dimensional spaces
The ratio of two probability density functions is becoming a quantity of interest these days in the machine learning and data mining communities since it can be used for various d...
Masashi Sugiyama, Motoaki Kawanabe, Pui Ling Chui
ESANN
2006
13 years 10 months ago
Margin based Active Learning for LVQ Networks
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...
BMCBI
2008
219views more  BMCBI 2008»
13 years 8 months ago
Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles
Background: Pancreatic cancer is the fourth leading cause of cancer death in the United States. Consequently, identification of clinically relevant biomarkers for the early detect...
Guangtao Ge, G. William Wong
CIKM
2010
Springer
13 years 6 months ago
Regularization and feature selection for networked features
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Hongliang Fei, Brian Quanz, Jun Huan
ADMA
2008
Springer
124views Data Mining» more  ADMA 2008»
13 years 10 months ago
Dimensionality Reduction for Classification
We investigate the effects of dimensionality reduction using different techniques and different dimensions on six two-class data sets with numerical attributes as pre-processing fo...
Frank Plastria, Steven De Bruyne, Emilio Carrizosa