cba v0.2-21

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Clustering for Business Analytics

Implements clustering techniques such as Proximus and Rock, utility functions for efficient computation of cross distances and data manipulation.

Functions in cba

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

Type Package
Encoding latin1
License GPL-2
NeedsCompilation yes
Packaged 2019-04-18 15:33:05 UTC; hornik
Repository CRAN
Date/Publication 2019-04-18 15:46:59 UTC

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