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AUSDM
2008
Springer
367views Data Mining» more  AUSDM 2008»
13 years 9 months ago
Categorical Proportional Difference: A Feature Selection Method for Text Categorization
Supervised text categorization is a machine learning task where a predefined category label is automatically assigned to a previously unlabelled document based upon characteristic...
Mondelle Simeon, Robert J. Hilderman
BMCBI
2004
181views more  BMCBI 2004»
13 years 7 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
CORR
2007
Springer
126views Education» more  CORR 2007»
13 years 7 months ago
Diversity-Multiplexing Tradeoff in Selective-Fading MIMO Channels
— We establish the optimal diversity-multiplexing (DM) tradeoff of coherent time, frequency and time-frequency selective-fading MIMO channels and provide a code design criterion ...
Pedro Coronel, Helmut Bölcskei
GECCO
2005
Springer
140views Optimization» more  GECCO 2005»
14 years 1 months ago
Stock prediction based on financial correlation
In this paper, we propose a neuro-genetic stock prediction system based on financial correlation between companies. A number of input variables are produced from the relatively h...
Yung-Keun Kwon, Sung-Soon Choi, Byung Ro Moon
JMLR
2010
104views more  JMLR 2010»
13 years 2 months ago
Increasing Feature Selection Accuracy for L1 Regularized Linear Models
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
Abhishek Jaiantilal, Gregory Z. Grudic