Veracity of Big Data by Vishnu Pendyala

Author:Vishnu Pendyala
Language: eng
Format: epub, pdf
Publisher: Apress, Berkeley, CA

In the general form, the terms in the above equation are all matrices and P k , Q, and R are covariance matrices. But for simplicity and for application to a single dimension time series of data values, we can assume them to be scalars and variances. Though their values depend on the domain, for simplicity, the initial values of the initial estimated mean is set to zero and apriori state variance P0 can be set to one or determined by intuition. The other variables in the above equation can then be computed recursively. Optimal values of the assumed constants Q and R can be obtained by applying the algorithm to what is known in the Machine Learning parlance as the “training data.” In the training data or ground truth, we already know which values are genuine and which are false. So, we calibrate the constants to achieve a high accuracy rate using this sample of known data.

Figure 4-5Kalman Filter interpreted as a Feedback Control System

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.