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ESANN
2007
13 years 5 months ago
Interval discriminant analysis using support vector machines
Imprecision, incompleteness, prior knowledge or improved learning speed can motivate interval–represented data. Most approaches for SVM learning of interval data use local kernel...
Cecilio Angulo, Davide Anguita, Luis Gonzál...
IJON
2006
119views more  IJON 2006»
13 years 3 months ago
Support vector machine for functional data classification
Abstract. Functional data analysis is a growing research field and numerous works present a generalization of the classical statistical methods to function classification or regres...
Fabrice Rossi, Nathalie Villa
BMCBI
2006
201views more  BMCBI 2006»
13 years 3 months ago
Gene selection algorithms for microarray data based on least squares support vector machine
Background: In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary ...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao
IJCNN
2006
IEEE
13 years 9 months 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...
INCDM
2010
Springer
308views Data Mining» more  INCDM 2010»
13 years 5 months ago
Data Mining with Neural Networks and Support Vector Machines Using the R/rminer Tool
We present rminer, our open source library for the R tool that facilitates the use of data mining (DM) algorithms, such as neural Networks (NNs) and support vector machines (SVMs),...
Paulo Cortez