jpiironen / gplite Goto Github PK
View Code? Open in Web Editor NEWGaussian process modeling in R
Gaussian process modeling in R
Hi, @jpiironen! I use gplite to take advantage of approximating GP by using LA.
I would model my data with a mean component that depends on another measured variable plus a latent variable GP. How can I combine the two things using gplite?
Thanks in advance
I don't see anywhere where the convergence results are stored. If we want to compute against this, we would have to handle the warning and pattern match the text for the appropriate message.
I'm thinking about using gplite
for the Bayesian optimization done in the tune
package. I'd like to pass in starting parameters since we run repeated GPs based in incremental updates to the data. My initial testing indicates that, for this application, taking a median or trimmed mean of the previous parameters is very helpful.
The issue is that it is difficult to know the parameter values for the covariance function (programmatically). I'd like to extract them per iteration but that might be difficult when there are compound covariance functions.
Can you make something like an extract_parameters
function that could return a data frame of the parameters and their associated covariance function? An update
method would also be nice.
For the example in the vignette, maybe something like this:
cf0 <- cf_const(magn = 5)
cf1 <- cf_lin(magn = 0.01)
cf2 <- cf_periodic(
period = 12,
prior_period = prior_fixed(),
) * cf_sexp(
lscale = 100,
magn = 1,
prior_magn = prior_fixed()
)
cfs <- list(cf0, cf1, cf2)
data.frame(
parameter = c("magn", "magn", "lscale", "magn"),
value = c(5, 0.01, 100, 1),
source = c("cf_const", "cf_lin", "cf_periodic", "cf_periodic"),
index = c(1, 1, 2, 2)
)
or something similar to make them identifiable and updatable.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.