# data setting
set.seed(1)
n = 1000 ; d = 1
m = 100
rho = 1
X = matrix(runif(n*d, 0, 1), nrow = n, ncol = d)
y = as.vector(sin(2*pi*X^3) + rnorm(n, 0, 0.1))
# Example for fastkrr
fit_pivoted = fastkrr(X, y,
kernel = "gaussian", opt = "pivoted",
m = 100, fastcv = TRUE, verbose = FALSE)
class(attr(fit_pivoted, "K"))
print(class(attr(fit_pivoted, "K")))
class(attr(fit_pivoted, "K_approx"))
print(class(attr(fit_pivoted, "K_approx")))
# Example for make_kernel
K = make_kernel(X, kernel = "gaussian", rho = rho)
class(K)
print(K)
# Example for make_kernel
K_rff = approx_kernel(X = X, opt = "rff", kernel = "gaussian",
d = d, rho = rho, n_threads = 1, m = 100)
class(attr(K_rff, "K_approx"))
print(attr(K_rff, "K_approx"))
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