diff options
Diffstat (limited to 'R/gensvm.grid.R')
| -rw-r--r-- | R/gensvm.grid.R | 12 |
1 files changed, 6 insertions, 6 deletions
diff --git a/R/gensvm.grid.R b/R/gensvm.grid.R index c541ea0..5fa026e 100644 --- a/R/gensvm.grid.R +++ b/R/gensvm.grid.R @@ -6,7 +6,7 @@ #' starts to speed up computation. The function uses the GenSVM C library for #' speed. #' -#' @param X training data matrix. We denote the size of this matrix by +#' @param x training data matrix. We denote the size of this matrix by #' n_samples x n_features. #' @param y training vector of class labes of length n_samples. The number of #' unique labels in this vector is denoted by n_classes. @@ -147,13 +147,13 @@ #' lambda=c(1e-8, 1e-6), max.iter=c(5000)) #' grid <- gensvm.grid(x, y, param.grid=pg, verbose=2) #' -gensvm.grid <- function(X, y, param.grid='tiny', refit=TRUE, scoring=NULL, cv=3, +gensvm.grid <- function(x, y, param.grid='tiny', refit=TRUE, scoring=NULL, cv=3, verbose=0, return.train.score=TRUE) { call <- match.call() - n.objects <- nrow(X) - n.features <- ncol(X) + n.objects <- nrow(x) + n.features <- ncol(x) n.classes <- length(unique(y)) if (n.objects != length(y)) { @@ -195,7 +195,7 @@ gensvm.grid <- function(X, y, param.grid='tiny', refit=TRUE, scoring=NULL, cv=3, } results <- .Call("R_gensvm_grid", - as.matrix(X), + data.matrix(x), as.integer(y.clean), as.matrix(C.param.grid), as.integer(nrow(C.param.grid)), @@ -225,7 +225,7 @@ gensvm.grid <- function(X, y, param.grid='tiny', refit=TRUE, scoring=NULL, cv=3, if (refit && !is.na(best.index)) { gensvm.args <- as.list(best.params) - gensvm.args$X <- X + gensvm.args$x <- x gensvm.args$y <- y gensvm.args$verbose <- if(verbose>1) 1 else 0 if (verbose > 1) |