GPTreeO - Dividing Local Gaussian Processes for Online Learning Regression
We implement and extend the Dividing Local Gaussian
Process algorithm by Lederer et al. (2020)
<doi:10.48550/arXiv.2006.09446>. Its main use case is in online
learning where it is used to train a network of local GPs
(referred to as tree) by cleverly partitioning the input space.
In contrast to a single GP, 'GPTreeO' is able to deal with
larger amounts of data. The package includes methods to create
the tree and set its parameter, incorporating data points from
a data stream as well as making joint predictions based on all
relevant local GPs.