How do I create these Kernel functions in Python for Gaussian Process Regression? - Printable Version +- Python Forum (https://python-forum.io) +-- Forum: Python Coding (https://python-forum.io/forum-7.html) +--- Forum: Data Science (https://python-forum.io/forum-44.html) +--- Thread: How do I create these Kernel functions in Python for Gaussian Process Regression? (/thread-26973.html)

How do I create these Kernel functions in Python for Gaussian Process Regression? - Shivam18 - May-20-2020 Hello all! I am new to this so I would appreciate any help. I have a dataset of 1031 observed samples of 7 features that form the X and one target variable that forms the Y. See below for input data and target representation with number of rows (n) and columns (m) mentioned in round brackets as (n x m). Here x1, x2, ..., x7 and y represent column vectors. X (1031 x 7) = [x1, x2, x3, ..., x7] Y (1031 x 1) = [y] I am using Gaussian Process Regressor to train my models. I want to use anisotropic Gaussian and anisotropic exponential correlation functions as kernels. Please see equation 14 and 15 in the attached equation pic for reference. How do I define these two functions in python such that they are compatible with SKlearns's GPR? Please help. -- Shivam