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» Support vector regression for classifier prediction
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112
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ICML
2005
IEEE
16 years 1 months ago
Explanation-Augmented SVM: an approach to incorporating domain knowledge into SVM learning
We introduce a novel approach to incorporating domain knowledge into Support Vector Machines to improve their example efficiency. Domain knowledge is used in an Explanation Based ...
Qiang Sun, Gerald DeJong
102
Voted
BMCBI
2004
133views more  BMCBI 2004»
15 years 18 days ago
Esub8: A novel tool to predict protein subcellular localizations in eukaryotic organisms
Background: Subcellular localization of a new protein sequence is very important and fruitful for understanding its function. As the number of new genomes has dramatically increas...
Qinghua Cui, Tianzi Jiang, Bing Liu, Songde Ma
94
Voted
NIPS
2007
15 years 2 months ago
Stability Bounds for Non-i.i.d. Processes
The notion of algorithmic stability has been used effectively in the past to derive tight generalization bounds. A key advantage of these bounds is that they are designed for spec...
Mehryar Mohri, Afshin Rostamizadeh
97
Voted
BMCBI
2006
110views more  BMCBI 2006»
15 years 24 days ago
Bias in error estimation when using cross-validation for model selection
Background: Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers...
Sudhir Varma, Richard Simon
143
Voted
TCBB
2008
138views more  TCBB 2008»
15 years 20 days ago
PairProSVM: Protein Subcellular Localization Based on Local Pairwise Profile Alignment and SVM
The subcellular locations of proteins are important functional annotations. An effective and reliable subcellular localization method is necessary for proteomics research. This pap...
Man-Wai Mak, Jian Guo, Sun-Yuan Kung