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» Prediction on Spike Data Using Kernel Algorithms
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ICML
2006
IEEE
15 years 10 months ago
Nonstationary kernel combination
The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...
ENC
2006
IEEE
15 years 3 months ago
Cleaning Training-Datasets with Noise-Aware Algorithms
We introduce a novel learning algorithm for noise elimination. Our algorithm is based on the re-measurement idea for the correction of erroneous observations and is able to discri...
H. Jair Escalante
KDD
2005
ACM
109views Data Mining» more  KDD 2005»
15 years 10 months ago
Formulating distance functions via the kernel trick
Tasks of data mining and information retrieval depend on a good distance function for measuring similarity between data instances. The most effective distance function must be for...
Gang Wu, Edward Y. Chang, Navneet Panda
ADMA
2006
Springer
153views Data Mining» more  ADMA 2006»
14 years 11 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
ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
14 years 11 months ago
Feature Selection for Nonlinear Kernel Support Vector Machines
An easily implementable mixed-integer algorithm is proposed that generates a nonlinear kernel support vector machine (SVM) classifier with reduced input space features. A single ...
Olvi L. Mangasarian, Gang Kou