| HAL-Inria | Publications, software ... of Inria's scientists |
Conference papers
A dimensionality reduction process to forecast events through stochastic models
Abstract : This paper describes a dimensionality reduction process to forecast time series events using stochastic models. As well as the KDD process defines a sequence of common steps to achieve useful information through data mining techniques, we propose a sequence of steps in order to estimate the probability of future events through stochastic modeling. Our process focus on reduce the dimension-ality of data, thus reducing the effect of the common problems involved in stochastic modeling, such as the state space explosion and the large modeling efforts to create such models.
Cited literature [30 references]
https://hal.inria.fr/hal-01247905
Contributor : Arnaud Legrand <>
Submitted on : Wednesday, December 23, 2015 - 9:42:24 AM
Last modification on : Tuesday, May 11, 2021 - 11:36:25 AM
Long-term archiving on: : Sunday, April 30, 2017 - 12:11:50 AM
Contributor : Arnaud Legrand <>
Submitted on : Wednesday, December 23, 2015 - 9:42:24 AM
Last modification on : Tuesday, May 11, 2021 - 11:36:25 AM
Long-term archiving on: : Sunday, April 30, 2017 - 12:11:50 AM
File
seke14paper_111.pdf
Files produced by the author(s)