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KLIEP_compute_score_cv <- function(sigma, x, y, centers, fold) {
phi_x <- compute_kernel_Gaussian(x, centers, sigma)
phi_y <- compute_kernel_Gaussian(y, centers, sigma)
mean_phi_y <- matrix(colMeans(phi_y))
nx <- nrow(x)
cv_split <- sample(nx) %% fold + 1
scores <- numeric(fold)
for (i in seq_len(fold)) {
alpha <- KLIEP_optimize_alpha(phi_x[cv_split != i, ], mean_phi_y = mean_phi_y)
scores[i] <- KLIEP_compute_score(phi_x[cv_split == i, ], alpha)
}
score_new <- mean(scores)
score_new
}
KLIEP_compute_score <- function(phi, alpha) {
mean(log(phi %*% alpha))
}
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