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CORR
2002
Springer
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13 years 4 months ago
Evaluating the Effectiveness of Ensembles of Decision Trees in Disambiguating Senseval Lexical Samples
This paper presents an evaluation of an ensemble
Ted Pedersen
ACL
1998
13 years 6 months ago
Classifier Combination for Improved Lexical Disambiguation
One of the most exciting recent directions in machine learning is the discovery that the combination of multiple classifiers often results in significantly better performance than...
Eric Brill, Jun Wu
DIS
2008
Springer
13 years 6 months ago
Unsupervised Classifier Selection Based on Two-Sample Test
We propose a well-founded method of ranking a pool of m trained classifiers by their suitability for the current input of n instances. It can be used when dynamically selecting a s...
Timo Aho, Tapio Elomaa, Jussi Kujala
ICPR
2002
IEEE
14 years 5 months ago
The Combining Classifier: To Train or Not to Train?
When more than a single classifier has been trained for the same recognition problem the question arises how this set of classifiers may be combined into a final decision rule. Se...
Robert P. W. Duin
ICPR
2004
IEEE
14 years 5 months ago
Segmentation and Classification of Meeting Events using Multiple Classifier Fusion and Dynamic Programming
In this paper the segmentation of a meeting into meeting events is investigated as well as the recognition of the detected segments. First the classification of a meeting event is...
Gerhard Rigoll, Stephan Reiter
ICIP
2005
IEEE
14 years 6 months ago
Combining classifiers for bone fracture detection in X-ray images
In medical applications, sensitivity in detecting medical problems and accuracy of detection are often in conflict. A single classifier usually cannot achieve both high sensitivit...
Vineta Lai Fun Lum, Wee Kheng Leow, Ying Chen, Tet...