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» Time series clustering based on forecast densities
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KDD
2008
ACM
159views Data Mining» more  KDD 2008»
15 years 10 months ago
Semi-supervised learning with data calibration for long-term time series forecasting
Many time series prediction methods have focused on single step or short term prediction problems due to the inherent difficulty in controlling the propagation of errors from one ...
Haibin Cheng, Pang-Ning Tan
IJON
2007
118views more  IJON 2007»
14 years 9 months ago
CATS benchmark time series prediction by Kalman smoother with cross-validated noise density
This article presents the winning solution to the CATS time series prediction competition. The solution is based on classical optimal linear estimation theory. The proposed method...
Simo Särkkä, Aki Vehtari, Jouko Lampinen
ISNN
2010
Springer
14 years 8 months ago
MULP: A Multi-Layer Perceptron Application to Long-Term, Out-of-Sample Time Series Prediction
Abstract. A forecasting approach based on Multi-Layer Perceptron (MLP) Artificial Neural Networks (named by the authors MULP) is proposed for the NN5 111 time series long-term, out...
Eros Pasero, Giovanni Raimondo, Suela Ruffa
SDM
2012
SIAM
285views Data Mining» more  SDM 2012»
13 years 3 days ago
A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time Series Datasets
Given the ubiquity of time series data, the data mining community has spent significant time investigating the best time series similarity measure to use for various tasks and dom...
Qiang Zhu 0002, Gustavo E. A. P. A. Batista, Thana...
FLAIRS
2004
14 years 11 months ago
A Method Based on RBF-DDA Neural Networks for Improving Novelty Detection in Time Series
Novelty detection in time series is an important problem with application in different domains such as machine failure detection, fraud detection and auditing. An approach to this...
Adriano L. I. Oliveira, Fernando Buarque de Lima N...