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» Computing and using residuals in time series models
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ML
2000
ACM
157views Machine Learning» more  ML 2000»
13 years 7 months ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins
IPPS
2007
IEEE
14 years 1 months ago
Time Series Forecasting by means of Evolutionary Algorithms
Many physical and artificial phenomena can be described by time series. The prediction of such phenomenon could be as complex as interesting. There are many time series forecasti...
Cristóbal Luque del Arco-Calderón, J...
IPPS
2008
IEEE
14 years 1 months ago
Modeling and predicting application performance on parallel computers using HPC challenge benchmarks
A method is presented for modeling application performance on parallel computers in terms of the performance of microkernels from the HPC Challenge benchmarks. Specifically, the a...
Wayne Pfeiffer, Nicholas J. Wright
WSC
2007
13 years 10 months ago
Folded standardized time series area variance estimators for simulation
We estimate the variance parameter of a stationary simulation-generated process using “folded” versions of standardized time series area estimators. We formulate improved vari...
Claudia Antonini, Christos Alexopoulos, David Gold...
KDD
2008
ACM
159views Data Mining» more  KDD 2008»
14 years 8 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