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ISNN
2011
Springer
12 years 10 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
BMCBI
2005
126views more  BMCBI 2005»
13 years 7 months ago
GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA
Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA struc...
Robert G. Beiko, Robert L. Charlebois
ICANN
2001
Springer
14 years 8 days ago
Generalized Relevance LVQ for Time Series
Abstract. An application of the recently proposed generalized relevance learning vector quantization (GRLVQ) to the analysis and modeling of time series data is presented. We use G...
Marc Strickert, Thorsten Bojer, Barbara Hammer
AINA
2008
IEEE
14 years 2 months ago
Missing Value Estimation for Time Series Microarray Data Using Linear Dynamical Systems Modeling
The analysis of gene expression time series obtained from microarray experiments can be effectively exploited to understand a wide range of biological phenomena from the homeostat...
Connie Phong, Raul Singh
JMLR
2008
144views more  JMLR 2008»
13 years 7 months ago
Search for Additive Nonlinear Time Series Causal Models
Pointwise consistent, feasible procedures for estimating contemporaneous linear causal structure from time series data have been developed using multiple conditional independence ...
Tianjiao Chu, Clark Glymour