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» Introduction to the Special Series
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IDA
2009
Springer
14 years 4 months ago
Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences
Abstract. This work aims to improve an existing time series forecasting algorithm –LBF– by the application of frequent episodes techniques as a complementary step to the model....
Francisco Martínez-Álvarez, Alicia T...
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
14 years 2 months ago
Grouped graphical Granger modeling methods for temporal causal modeling
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
CSDA
2008
56views more  CSDA 2008»
13 years 10 months ago
Robust designs for series estimation
We discuss optimal design problems for a popular method of series estimation in regression problems. Commonly used design criteria are based on the generalized variance of the est...
Holger Dette, Douglas P. Wiens
ILP
2000
Springer
14 years 1 months ago
Learning First Order Logic Time Series Classifiers
A method for learning multivariate time series classifiers by inductive logic programming is presented. Two types of background predicate that are suited for this task are introduc...
Juan José Rodríguez, Carlos J. Alons...
KDD
2006
ACM
153views Data Mining» more  KDD 2006»
14 years 10 months ago
Semi-supervised time series classification
The problem of time series classification has attracted great interest in the last decade. However current research assumes the existence of large amounts of labeled training data...
Li Wei, Eamonn J. Keogh