5 files changed, 24 insertions, 22 deletions

diff --git a/man/gensvm.Rd b/man/gensvm.Rd
index 5aabcaa..e48444f 100644
--- a/man/gensvm.Rd
+++ b/man/gensvm.Rd
@@ -24,8 +24,9 @@ function (i.e. \code{model.matrix( ~ var - 1)}).}
 \item{kappa}{parameter for the hinge function in the loss function (kappa > 
 -1.0)}
 
-\item{weights}{type of instance weights to use. Options are 'unit' for unit 
-weights and 'group' for group size correction weight (eq. 4 in the paper).}
+\item{weights}{type or vector of instance weights to use. Options are 'unit' 
+for unit weights and 'group' for group size correction weights (eq. 4 in the 
+paper). Alternatively, a vector of weights can be provided.}
 
 \item{kernel}{the kernel type to use in the classifier. It must be one of 
 'linear', 'poly', 'rbf', or 'sigmoid'. See the section "Kernels in GenSVM" 
diff --git a/man/gensvm.grid.Rd b/man/gensvm.grid.Rd
index cc44286..b365e10 100644
--- a/man/gensvm.grid.Rd
+++ b/man/gensvm.grid.Rd
@@ -4,11 +4,11 @@
 \alias{gensvm.grid}
 \title{Cross-validated grid search for GenSVM}
 \usage{
-gensvm.grid(X, y, param.grid = "tiny", refit = TRUE, scoring = NULL,
+gensvm.grid(x, y, param.grid = "tiny", refit = TRUE, scoring = NULL,
   cv = 3, verbose = 0, return.train.score = TRUE)
 }
 \arguments{
-\item{X}{training data matrix. We denote the size of this matrix by 
+\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 
diff --git a/man/plot.gensvm.Rd b/man/plot.gensvm.Rd
index a958c4d..9c15bea 100644
--- a/man/plot.gensvm.Rd
+++ b/man/plot.gensvm.Rd
@@ -4,18 +4,15 @@
 \alias{plot.gensvm}
 \title{Plot the simplex space of the fitted GenSVM model}
 \usage{
-\method{plot}{gensvm}(fit, x, y.true = NULL, with.margins = TRUE,
+\method{plot}{gensvm}(fit, y, x.test = NULL, with.margins = TRUE,
   with.shading = TRUE, with.legend = TRUE, center.plot = TRUE,
   xlim = NULL, ylim = NULL, ...)
 }
 \arguments{
 \item{fit}{A fitted \code{gensvm} object}
 
-\item{x}{the dataset to plot}
-
-\item{y.true}{the true data labels. If provided the objects will be colored 
-using the true labels instead of the predicted labels. This makes it easy to 
-identify misclassified objects.}
+\item{y}{the labels to color points with (if NULL the predicted labels are 
+used)}
 
 \item{with.margins}{plot the margins}
 
@@ -34,6 +31,8 @@ bounds will be used for the vertical axis and the value of center.plot will
 be ignored}
 
 \item{...}{further arguments are passed to the builtin plot() function}
+
+\item{x}{the dataset to plot (if NULL the training data is used)}
 }
 \value{
 returns the object passed as input
@@ -52,16 +51,16 @@ y <- iris[, 5]
 fit <- gensvm(x, y)
 
 # plot the simplex space
-plot(fit, x)
+plot(fit)
 
 # plot and use the true colors (easier to spot misclassified samples)
-plot(fit, x, y.true=y)
+plot(fit, y)
 
 # plot only misclassified samples
-x.mis <- x[predict(fit, x) != y, ]
-y.mis.true <- y[predict(fit, x) != y]
-plot(fit, x.mis)
-plot(fit, x.mis, y.true=y.mis.true)
+x.mis <- x[predict(fit) != y, ]
+y.mis.true <- y[predict(fit) != y]
+plot(fit, x.test=x.mis)
+plot(fit, y.mis.true, x.test=x.mis)
 
 }
 \author{
diff --git a/man/plot.gensvm.grid.Rd b/man/plot.gensvm.grid.Rd
index 0db01ec..3e5ef39 100644
--- a/man/plot.gensvm.grid.Rd
+++ b/man/plot.gensvm.grid.Rd
@@ -4,14 +4,14 @@
 \alias{plot.gensvm.grid}
 \title{Plot the simplex space of the best fitted model in the GenSVMGrid}
 \usage{
-\method{plot}{gensvm.grid}(grid, x, ...)
+\method{plot}{gensvm.grid}(grid, ...)
 }
 \arguments{
 \item{grid}{A \code{gensvm.grid} object trained with refit=TRUE}
 
-\item{x}{the dataset to plot}
-
 \item{...}{further arguments are passed to the plot function}
+
+\item{x}{the dataset to plot}
 }
 \value{
 returns the object passed as input
diff --git a/man/predict.gensvm.Rd b/man/predict.gensvm.Rd
index 2881e26..0b82662 100644
--- a/man/predict.gensvm.Rd
+++ b/man/predict.gensvm.Rd
@@ -5,13 +5,15 @@
 \alias{predict.gensvm}
 \title{Predict class labels with the GenSVM model}
 \usage{
-\method{predict}{gensvm}(fit, x.test, ...)
+\method{predict}{gensvm}(fit, newdata, add.rownames = FALSE, ...)
 }
 \arguments{
 \item{fit}{Fitted \code{gensvm} object}
 
-\item{x.test}{Matrix of new values for \code{x} for which predictions need 
-to be made.}
+\item{newdata}{Matrix of new data for which predictions need to be made.}
+
+\item{add.rownames}{add the rownames from the training data to the 
+predictions}
 
 \item{\dots}{further arguments are ignored}
 }