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» Support Vector Classification with Input Data Uncertainty
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ADMA
2006
Springer
153views Data Mining» more  ADMA 2006»
13 years 9 months ago
An Effective Combination Based on Class-Wise Expertise of Diverse Classifiers for Predictive Toxicology Data Mining
This paper presents a study on the combination of different classifiers for toxicity prediction. Two combination operators for the Multiple-Classifier System definition are also pr...
Daniel Neagu, Gongde Guo, Shanshan Wang
IJCNN
2006
IEEE
14 years 1 months ago
Adaptation of Artificial Neural Networks Avoiding Catastrophic Forgetting
— In connectionist learning, one relevant problem is “catastrophic forgetting” that may occur when a network, trained with a large set of patterns, has to learn new input pat...
Dario Albesano, Roberto Gemello, Pietro Laface, Fr...
ICDM
2007
IEEE
248views Data Mining» more  ICDM 2007»
13 years 11 months ago
Adapting SVM Classifiers to Data with Shifted Distributions
Many data mining applications can benefit from adapting existing classifiers to new data with shifted distributions. In this paper, we present Adaptive Support Vector Machine (Ada...
Jun Yang 0003, Rong Yan, Alexander G. Hauptmann
ISCIS
2005
Springer
14 years 1 months ago
Classification of Volatile Organic Compounds with Incremental SVMs and RBF Networks
Support Vector Machines (SVMs) have been applied to solve the classification of volatile organic compounds (VOC) data in some recent studies. SVMs provide good generalization perfo...
Zeki Erdem, Robi Polikar, Nejat Yumusak, Fikret S....
BMCBI
2006
158views more  BMCBI 2006»
13 years 7 months ago
Detection of non-coding RNAs on the basis of predicted secondary structure formation free energy change
Background: Non-coding RNAs (ncRNAs) have a multitude of roles in the cell, many of which remain to be discovered. However, it is difficult to detect novel ncRNAs in biochemical s...
Andrew V. Uzilov, Joshua M. Keegan, David H. Mathe...