animate_glmnet | R Documentation |
This function visualizes the a cv.glmnet machine learning process.
animate_glmnet(cv.glmnet, replay = FALSE, plot.cv = TRUE,
total.time = ifelse(plot.cv, 15, 10), new.save = TRUE, save = "html",
debug = FALSE, debug.n = 10, captions = FALSE, alt.captions = FALSE,
transition.n = 10, ...)
cv.glmnet |
An object of class 'cv.glmnet' |
replay |
Should the animation be replayed in the visual device? Defaults to FALSE. |
plot.cv |
Should cross-validation be plotted? Defaults to TRUE. |
total.time |
Desired time of animation in seconds. Defaults to 15 if plot.cv selected, else 10. |
new.save |
Should this animation be saved as a new object rather than overwrite the preceeding animation? Defaults to TRUE. |
save |
Save as "html" or "gif"? Defaults to "html". |
debug |
Only plot subset of lambda values? Defaults to FALSE. |
debug.n |
If plotting subset of lambda values, sets number of values to plot. Defaults to 10. |
captions |
Should captions be added to animation? Defaults to FALSE. |
transition.n |
How many frames should be used to transition between cross-validation and model fit? Defaults to 10. |
... |
Options passed to saveHTML or saveGIF functions. See ?animate::saveHTML and ?animate::saveGIF |
captions.alt |
Should alternative captions be added to animation? Defaults to FALSE. |
# See also: ?cv.glmnet:
set.seed(1010)
n=1000;p=100
nzc=trunc(p/10)
x=matrix(rnorm(n*p),n,p)
beta=rnorm(nzc)
fx= x[,seq(nzc)] %*% beta
eps=rnorm(n)*5
y=drop(fx+eps)
px=exp(fx)
px=px/(1+px)
ly=rbinom(n=length(px),prob=px,size=1)
set.seed(1011)
cvob1=cv.glmnet(x,y)
animate_glmnet(cvob1)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.