Sciweavers

Free Online Productivity Tools i2Speak i2Symbol i2OCR iTex2Img iWeb2Print iWeb2Shot i2Type iPdf2Split iPdf2Merge i2Bopomofo i2Arabic i2Style i2Image i2PDF iLatex2Rtf Sci2ools

10

MCS
2000
Springer

favoriteEmaildiscussreport

109views Pattern Recognition» more MCS 2000»

Experiments with Classifier Combining Rules

13 years 8 months ago

Experiments with Classifier Combining Rules

Download homepage.tudelft.nl

Abstract. A large experiment on combining classifiers is reported and discussed. It includes, both, the combination of different classifiers on the same feature set and the combination of classifiers on different feature sets. Various fixed and trained combining rules are used. It is shown that there is no overall winning combining rule and that bad classifiers as well as bad feature sets may contain valuable information for performance improvement by combining rules. Best performance is achieved by combining both, different feature sets and different classifiers.

Robert P. W. Duin, David M. J. Tax

Real-time Traffic

Feature Sets | MCS 2000 | Pattern Recognition | Winning Combining Rule |

claim paper

Related Content

» Comparing Combination Rules of Pairwise Neural Networks Classifiers

» Combining Neural Networks Based on DempsterShafer Theory for Classifying Data with Imperfe...

» Classifier Combining Rules Under Independence Assumptions

» Avoiding Data Overfitting in Scientific Discovery Experiments in Functional Genomics

» A Discussion on the Classifier Projection Space for Classifier Combining

» Rejection Strategies and Confidence Measures for a k NN Classifier in an OCR Task

» Analysis of Linear and Order Statistics Combiners for Fusion of Imbalanced Classifiers

» Cancer Prediction Using DiversityBased Ensemble Genetic Programming

» Combining Fisher Linear Discriminants for Dissimilarity Representations

Post Info
More Details (n/a)

Added	25 Aug 2010
Updated	25 Aug 2010
Type	Conference
Year	2000
Where	MCS
Authors	Robert P. W. Duin, David M. J. Tax

Comments (0)