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ICML
2002
IEEE
14 years 9 months ago
Is Combining Classifiers Better than Selecting the Best One
We empirically evaluate several state-of-theart methods for constructing ensembles of heterogeneous classifiers with stacking and show that they perform (at best) comparably to se...
Saso Dzeroski, Bernard Zenko
ESANN
2008
13 years 10 months ago
Interpretable ensembles of local models for safety-related applications
Abstract. This paper discusses a machine learning approach for binary classification problems which satisfies the specific requirements of safety-related applications. The approach...
Sebastian Nusser, Clemens Otte, Werner Hauptmann
WWW
2011
ACM
13 years 3 months ago
Parallel boosted regression trees for web search ranking
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal...
EH
1999
IEEE
351views Hardware» more  EH 1999»
14 years 1 months ago
Evolvable Hardware or Learning Hardware? Induction of State Machines from Temporal Logic Constraints
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
PPSN
1990
Springer
14 years 1 months ago
Feature Construction for Back-Propagation
T h e ease of learning concepts f r o m examples in empirical machine learning depends on the attributes used for describing the training d a t a . We show t h a t decision-tree b...
Selwyn Piramuthu