R: Clustering for Business Analytics

# Clustering for Business Analytics

## Documentation for package ‘cba’ version 0.2-21

- DESCRIPTION file.

## Help Pages

as.dummy | Dummy Coding
as.dummy.data.frame | Dummy Coding
as.dummy.matrix | Dummy Coding
ccfkms | Clustering with Conjugate Convex Functions
circleplot.dist | Plotting Distance Graphs
clmplot | Plotting Logical Matrices
cluster.dist | Clustering a Sparse Symmetric Distance Matrix
cut.ordered | Converting Ordered Factors
fitted.proximus | Extract from a Proximus Object
fitted.rock | Rock Clustering
gknn | Generalized k-Nearest Neighbor Classification
implot | Matrix Image Plots
lminter | Interpolating Logical Matrices
lmplot | Plotting Logical Matrices
Mushroom | Mushroom Data Set
order.data.frame | Improving the Presentation of Matrix Objects
order.dist | Improving the Presentation of Matrix Objects
order.greedy | Hierarchical Greedy Ordering
order.length | Conciseness of Presentation Measures
order.matrix | Improving the Presentation of Matrix Objects
order.optimal | Optimal Leaf Ordering of Binary Trees.
plot.sdists.graph | Plotting Edit Transcripts and Sequence Alignments
predict.ccfkms | Clustering with Conjugate Convex Functions.
predict.rock | Rock Clustering
print.summary.proximus | Summarizing Proximus Objects
proximus | Proximus
rlbmat | Block Uniform Logical Matrix Deviates
rockCluster | Rock Clustering
rockLink | Rock Clustering
sdists | Sequence Distance Computation
sdists.center | Centroid Sequences
sdists.center.align | Align Sequences to a Center
sdists.trace | Edit Transcripts and Sequence Alignments
stress | Conciseness of Presentation Measures
stress.dist | Conciseness of Presentation Measures
summary.proximus | Summarizing Proximus Objects
townships | Bertin's Characteristics and Townships Data Set
Votes | Congressional Votes 1984 Data Set