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TSP
2010
14 years 4 months ago
Bayesian multi-object filtering with amplitude feature likelihood for unknown object SNR
In many tracking scenarios, the amplitude of target returns are stronger than those coming from false alarms. This information can be used to improve the multi-target state estimat...
Daniel Clark, Branko Ristic, Ba-Ngu Vo, Ba-Tuong V...
BMCBI
2008
109views more  BMCBI 2008»
14 years 9 months ago
MetaFIND: A feature analysis tool for metabolomics data
Background: Metabolomics, or metabonomics, refers to the quantitative analysis of all metabolites present within a biological sample and is generally carried out using NMR spectro...
Kenneth Bryan, Lorraine Brennan, Padraig Cunningha...
KDD
2004
ACM
151views Data Mining» more  KDD 2004»
15 years 10 months ago
Feature selection in scientific applications
Numerous applications of data mining to scientific data involve the induction of a classification model. In many cases, the collection of data is not performed with this task in m...
Erick Cantú-Paz, Shawn Newsam, Chandrika Ka...
TAL
2010
Springer
14 years 7 months ago
Summarization as Feature Selection for Document Categorization on Small Datasets
Abstract. Most common feature selection techniques for document categorization are supervised and require lots of training data in order to accurately capture the descriptive and d...
Emmanuel Anguiano-Hernández, Luis Villase&n...
JMLR
2010
104views more  JMLR 2010»
14 years 4 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