Visualizing Classification Results


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Documentation for package ‘classmap’ version 1.2.0

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
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.