Description Usage Arguments Details Value Examples
This function computes the instantaneous loss (i.e., squared Euclidean distantce) of an observation to its nearest center within a set of centers.
1 | instantaneous_loss(centers, instant_observation)
|
centers |
a matrix containing m centers of length d, where each row corresponds to d coordinates of a center. |
instant_observation |
a vector of length d. |
Given a set C of m centers of length d (i.e., C = {c_{1}, c_{2}, …, c_{m}}) and a vector observation x of length d, this function computes the squared euclidean distance of x to its nearest center within C, i.e.,
L(x,C) = min_{1<= i <= m}|x-c_{i}|_{2}^{2}.
The squared Euclidean distance of instant_observation
to its nearest center within centers
.
1 2 3 4 | ## generating 4 centers of length 3.
centers <- matrix(1:12, nrow = 4, ncol = 3)
instant_observation <- c(2,6,10)
instantaneous_loss(centers, instant_observation)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.