albinali wrote: > - I am suggesting to eliminate highly dependent variables to avoid having > the same evidence from different source, for example, a light intensity > sensor is likely to be correlated with a sensor that detects if the curtains > on a window are open, using both sensors as evidence sources to infer a > particular activity ex. a breakfast might erroneously increase the belief > about a breakfast activity taking place while infact both sensors are > reflecting the same evidence. Thats why I need to filter them out. But again > maybe I am missing something
No, no and no. The Bayesian Networks and most modelling tools do not work the way you think they work ... redundant evidence does not make worse predictions, despite your belief that they do. -- Paige Miller Eastman Kodak Company [EMAIL PROTECTED] http://www.kodak.com "It's nothing until I call it!" -- Bill Klem, NL Umpire "When you get the choice to sit it out or dance, I hope you dance" -- Lee Ann Womack . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
