7 search results - page 1 / 2 » Using causal discovery for feature selection in multivariate... |
KDD
2009
ACM
14 years 5 months ago
2009
ACM
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
ICDM
2006
IEEE
13 years 11 months ago
2006
IEEE
Several spatio-temporal data collected in many applications, such as fMRI data in medical applications, can be represented as a Multivariate Time Series (MTS) matrix with m rows (...
BMCBI
2007
13 years 5 months ago
2007
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
KDD
2009
ACM
13 years 9 months ago
2009
ACM
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...
KDD
2009
ACM
13 years 11 months ago
2009
ACM
To discover patterns in historical data, climate scientists have applied various clustering methods with the goal of identifying regions that share some common climatological beha...