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» CLOUDS: A Decision Tree Classifier for Large Datasets
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ICML
2001
IEEE
14 years 6 months ago
Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers
Accurate, well-calibrated estimates of class membership probabilities are needed in many supervised learning applications, in particular when a cost-sensitive decision must be mad...
Bianca Zadrozny, Charles Elkan
BMCBI
2008
115views more  BMCBI 2008»
13 years 6 months ago
Improving peptide-MHC class I binding prediction for unbalanced datasets
Background: Establishment of peptide binding to Major Histocompatibility Complex class I (MHCI) is a crucial step in the development of subunit vaccines and prediction of such bin...
Ana Paula Sales, Georgia D. Tomaras, Thomas B. Kep...
BMCBI
2008
71views more  BMCBI 2008»
13 years 6 months ago
Examining the significance of fingerprint-based classifiers
Background: Experimental examinations of biofluids to measure concentrations of proteins or their fragments or metabolites are being explored as a means of early disease detection...
Brian T. Luke, Jack R. Collins
ICIP
2009
IEEE
13 years 3 months ago
An incremental extremely random forest classifier for online learning and tracking
Decision trees have been widely used for online learning classification. Many approaches usually need large data stream to finish decision trees induction, as show notable limitat...
Aiping Wang, Guowei Wan, Zhiquan Cheng, Sikun Li
DIS
2004
Springer
13 years 9 months ago
Generating AVTs Using GA for Learning Decision Tree Classifiers with Missing Data
Abstract. Attribute value taxonomies (AVTs) have been used to perform AVT-guided decision tree learning on partially or totally missing data. In many cases, user-supplied AVTs are ...
Jinu Joo, Jun Zhang 0002, Jihoon Yang, Vasant Hona...