fix spelling

4 files changed, 6 insertions, 6 deletions

diff --git a/R/gensvm.grid.R b/R/gensvm.grid.R
index 8fa187e..599b588 100644
--- a/R/gensvm.grid.R
+++ b/R/gensvm.grid.R
@@ -8,7 +8,7 @@
 #'
 #' @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 
+#' @param y training vector of class labels of length n_samples. The number of 
 #' unique labels in this vector is denoted by n_classes.
 #' @param param.grid String (\code{'tiny'}, \code{'small'}, or \code{'full'}) 
 #' or data frame with parameter configurations to evaluate.  Typically this is 
@@ -48,7 +48,7 @@
 #' \item{cv.idx}{Array with cross validation indices used to split the data}
 #'
 #' @section Using a Parameter Grid:
-#' To evaluate certain paramater configurations, a data frame can be supplied 
+#' To evaluate certain parameter configurations, a data frame can be supplied 
 #' to the \code{param.grid} argument of the function. Such a data frame can 
 #' easily be generated using the R function \code{expand.grid}, or could be 
 #' created through other ways to test specific parameter configurations.
diff --git a/R/gensvm.maxabs.scale.R b/R/gensvm.maxabs.scale.R
index 47a6340..0c0f6f3 100644
--- a/R/gensvm.maxabs.scale.R
+++ b/R/gensvm.maxabs.scale.R
@@ -1,6 +1,6 @@
 #' @title Scale each column of a matrix by its maximum absolute value
 #'
-#' @description Scaling a dataset can creatly decrease the computation time of 
+#' @description Scaling a dataset can greatly decrease the computation time of 
 #' GenSVM. This function scales the data by dividing each column of a matrix by 
 #' the maximum absolute value of that column. This preserves sparsity in the 
 #' data while mapping each column to the interval [-1, 1].
diff --git a/man/gensvm.grid.Rd b/man/gensvm.grid.Rd
index a19b631..94cdcd5 100644
--- a/man/gensvm.grid.Rd
+++ b/man/gensvm.grid.Rd
@@ -11,7 +11,7 @@ gensvm.grid(x, y, param.grid = "tiny", refit = TRUE, scoring = NULL,
 \item{x}{training data matrix. We denote the size of this matrix by 
 n_samples x n_features.}
 
-\item{y}{training vector of class labes of length n_samples. The number of 
+\item{y}{training vector of class labels of length n_samples. The number of 
 unique labels in this vector is denoted by n_classes.}
 
 \item{param.grid}{String (\code{'tiny'}, \code{'small'}, or \code{'full'}) 
@@ -70,7 +70,7 @@ the user.
 }
 \section{Using a Parameter Grid}{
 
-To evaluate certain paramater configurations, a data frame can be supplied 
+To evaluate certain parameter configurations, a data frame can be supplied 
 to the \code{param.grid} argument of the function. Such a data frame can 
 easily be generated using the R function \code{expand.grid}, or could be 
 created through other ways to test specific parameter configurations.
diff --git a/man/gensvm.maxabs.scale.Rd b/man/gensvm.maxabs.scale.Rd
index cbbfd29..7c75eff 100644
--- a/man/gensvm.maxabs.scale.Rd
+++ b/man/gensvm.maxabs.scale.Rd
@@ -18,7 +18,7 @@ is supplied, a list with elements \code{x} and \code{x.test} representing
 the scaled datasets.
 }
 \description{
-Scaling a dataset can creatly decrease the computation time of 
+Scaling a dataset can greatly decrease the computation time of 
 GenSVM. This function scales the data by dividing each column of a matrix by 
 the maximum absolute value of that column. This preserves sparsity in the 
 data while mapping each column to the interval [-1, 1].