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» On Combining Classifiers
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ICPR
2004
IEEE
16 years 3 months ago
A Trainable Low-level Feature Detector
We introduce a trainable system that simultaneously filters and classifies low-level features into types specified by the user. The system operates over full colour images, and ou...
John P. Collomosse, Martin Owen, Peter M. Hall
116
Voted
ICPR
2000
IEEE
16 years 3 months ago
Measuring the Complexity of Classification Problems
We studied a number of measures that characterize the difficulty of a classification problem. We compared a set of real world problems to random combinations of points in this mea...
Tin Kam Ho, Mitra Basu
ICML
2007
IEEE
16 years 3 months ago
On learning with dissimilarity functions
We study the problem of learning a classification task in which only a dissimilarity function of the objects is accessible. That is, data are not represented by feature vectors bu...
Liwei Wang, Cheng Yang, Jufu Feng
106
Voted
ICTAI
2007
IEEE
15 years 8 months ago
Accurate Classification of SAGE Data Based on Frequent Patterns of Gene Expression
In this paper we present a method for classifying accurately SAGE (Serial Analysis of Gene Expression) data. The high dimensionality of the data, namely the large number of featur...
George Tzanis, Ioannis P. Vlahavas
122
Voted
MCS
2007
Springer
15 years 8 months ago
Stopping Criteria for Ensemble-Based Feature Selection
Selecting the optimal number of features in a classifier ensemble normally requires a validation set or cross-validation techniques. In this paper, feature ranking is combined with...
Terry Windeatt, Matthew Prior