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» Complexity measures and decision tree complexity: a survey
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PRL
2008
213views more  PRL 2008»
13 years 8 months ago
Boosting recombined weak classifiers
Boosting is a set of methods for the construction of classifier ensembles. The differential feature of these methods is that they allow to obtain a strong classifier from the comb...
Juan José Rodríguez, Jesús Ma...
RECOMB
2009
Springer
14 years 9 months ago
Finding Biologically Accurate Clusterings in Hierarchical Tree Decompositions Using the Variation of Information
Abstract. Hierarchical clustering is a popular method for grouping together similar elements based on a distance measure between them. In many cases, annotation information for som...
Saket Navlakha, James Robert White, Niranjan Nagar...
STACS
2005
Springer
14 years 2 months ago
Robust Polynomials and Quantum Algorithms
We define and study the complexity of robust polynomials for Boolean functions and the related fault-tolerant quantum decision trees, where input bits are perturbed by noise. We ...
Harry Buhrman, Ilan Newman, Hein Röhrig, Rona...
BMCBI
2008
115views more  BMCBI 2008»
13 years 8 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...
NAACL
1994
13 years 9 months ago
Tree-Based State Tying for High Accuracy Modelling
The key problem to be faced when building a HMM-based continuous speech recogniser is maintaining the balance between model complexity and available training data. For large vocab...
S. J. Young, J. J. Odell, Philip C. Woodland