# Visualizing Classification Results

## Documentation for package ‘classmap’ version 1.2.6

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

classmap | Draw the class map to visualize classification results.
confmat.vcr | Build a confusion matrix from the output of a function 'vcr.*.*'.
data_bookReviews | Amazon book reviews data
data_floralbuds | Floral buds data
data_instagram | Instagram data
data_titanic | Titanic data
makeFV | Constructs feature vectors from a kernel matrix.
makeKernel | Compute kernel matrix
predscor | Draws a predictions correlation plot, which visualizes the correlations between the prediction terms in a regression fit.
predsplot | Make a predictions plot
qresplot | Draw a quasi residual plot of PAC versus a data feature
silplot | Draw the silhouette plot of a classification
stackedplot | Make a vertically stacked mosaic plot of class predictions.
vcr.da.newdata | Carry out discriminant analysis on new data, and prepare to visualize its results.
vcr.da.train | Carry out discriminant analysis on training data, and prepare to visualize its results.
vcr.forest.newdata | Prepare for visualization of a random forest classification on new data.
vcr.forest.train | Prepare for visualization of a random forest classification on training data
vcr.knn.newdata | Carry out a k-nearest neighbor classification on new data, and prepare to visualize its results.
vcr.knn.train | Carry out a k-nearest neighbor classification on training data, and prepare to visualize its results.
vcr.neural.newdata | Prepare for visualization of a neural network classification on new data.
vcr.neural.train | Prepare for visualization of a neural network classification on training data.
vcr.rpart.newdata | Prepare for visualization of an rpart classification on new data.
vcr.rpart.train | Prepare for visualization of an rpart classification on training data.
vcr.svm.newdata | Prepare for visualization of a support vector machine classification on new data.
vcr.svm.train | Prepare for visualization of a support vector machine classification on training data.