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» Complexity measures and decision tree complexity: a survey
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PRL
2008
213views more  PRL 2008»
15 years 6 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
16 years 6 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
15 years 11 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»
15 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...
NAACL
1994
15 years 7 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