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ICPR
2004
IEEE
16 years 7 months ago
The Characterization of Classification Problems by Classifier Disagreements
In this paper we try to characterize a set of classification problems. For this, we use the disagreement between a set of standard classifiers. The disagreement patterns do not on...
David M. J. Tax, Elzbieta Pekalska, Robert P. W. D...
ICPR
2008
IEEE
16 years 23 days ago
Pre-extracting method for SVM classification based on the non-parametric K-NN rule
With the increase of the training set’s size, the efficiency of support vector machine (SVM) classifier will be confined. To solve such a problem, a novel preextracting method f...
Deqiang Han, Chongzhao Han, Yi Yang, Yu Liu, Wenta...
IJCNN
2006
IEEE
16 years 10 days ago
Classify Unexpected News Impacts to Stock Price by Incorporating Time Series Analysis into Support Vector Machine
— the paper discusses an approach of using traditional time series analysis, as domain knowledge, to help the data-preparation of support vector machine for classifying documents...
Ting Yu, Tony Jan, John K. Debenham, Simeon J. Sim...
FLAIRS
2004
15 years 7 months ago
Transductive LSI for Short Text Classification Problems
This paper presents work that uses Transductive Latent Semantic Indexing (LSI) for text classification. In addition to relying on labeled training data, we improve classification ...
Sarah Zelikovitz
ISMB
1993
15 years 7 months ago
Knowledge-Based Generation of Machine-Learning Experiments: Learning with DNA Crystallography Data
Thoughit has been possible in the past to learn to predict DNAhydration patterns from crystallographic data, there is ambiguity in the choice of training data (both in terms of th...
Dawn M. Cohen, Casimir A. Kulikowski, Helen Berman