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» Support Vector Regression Machines
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85
Voted
BMCBI
2007
119views more  BMCBI 2007»
15 years 16 days ago
Efficacy of different protein descriptors in predicting protein functional families
Background: Sequence-derived structural and physicochemical descriptors have frequently been used in machine learning prediction of protein functional families, thus there is a ne...
Serene A. K. Ong, Hong Huang Lin, Yu Zong Chen, Ze...
141
Voted
ML
2008
ACM
248views Machine Learning» more  ML 2008»
15 years 14 days ago
Feature selection via sensitivity analysis of SVM probabilistic outputs
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
16 years 28 days ago
Extracting key-substring-group features for text classification
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Dell Zhang, Wee Sun Lee
93
Voted
BMCBI
2010
146views more  BMCBI 2010»
15 years 19 days ago
Nonnegative principal component analysis for mass spectral serum profiles and biomarker discovery
Background: As a novel cancer diagnostic paradigm, mass spectroscopic serum proteomic pattern diagnostics was reported superior to the conventional serologic cancer biomarkers. Ho...
Henry Han
127
Voted
BMCBI
2005
131views more  BMCBI 2005»
15 years 12 days ago
Regularized Least Squares Cancer Classifiers from DNA microarray data
Background: The advent of the technology of DNA microarrays constitutes an epochal change in the classification and discovery of different types of cancer because the information ...
Nicola Ancona, Rosalia Maglietta, Annarita D'Addab...