Rdocumentation
powered by
Learn R Programming
cba (version 0.2-25)
Clustering for Business Analytics
Description
Implements clustering techniques such as Proximus and Rock, utility functions for efficient computation of cross distances and data manipulation.
Copy Link
Link to current version
Version
Version
0.2-25
0.2-24
0.2-23
0.2-22
0.2-21
0.2-20
0.2-19
0.2-18
0.2-17
0.2-16
0.2-15
0.2-14
0.2-13
0.2-12
0.2-11
0.2-10
0.2-9
0.2-8
0.2-7
0.2-6
0.2-5
0.2-4
0.2-2
0.2-1
0.2-0
0.1-8
0.1-7
0.1-6
0.1-5
0.1-3
Install
install.packages('cba')
Monthly Downloads
2,596
Version
0.2-25
License
GPL-2
Maintainer
Christian Buchta
Last Published
August 16th, 2024
Functions in cba (0.2-25)
Search all functions
lminter
Interpolating Logical Matrices
plot.sdists.graph
Plotting Edit Transcripts and Sequence Alignments
proximus
Proximus
sdists.trace
Edit Transcripts and Sequence Alignments
summary.proximus
Summarizing Proximus Objects
sdists
Sequence Distance Computation
sdists.center
Centroid Sequences
rlbmat
Block Uniform Logical Matrix Deviates
townships
Bertin's Characteristics and Townships Data Set
sdists.center.align
Align Sequences to a Center
stress
Conciseness of Presentation Measures
rockCluster
Rock Clustering
clmplot
Plotting Logical Matrices
coding
Dummy Coding
Votes
Congressional Votes 1984 Data Set
cut.ordered
Converting Ordered Factors
Mushroom
Mushroom Data Set
fitted.proximus
Extract from a Proximus Object
cluster.dist
Clustering a Sparse Symmetric Distance Matrix
gknn
Generalized k-Nearest Neighbor Classification
order.optimal
Optimal Leaf Ordering of Binary Trees.
image
Matrix Image Plots
order.greedy
Hierarchical Greedy Ordering
order.length
Conciseness of Presentation Measures
predict.ccfkms
Clustering with Conjugate Convex Functions.
predict.rock
Rock Clustering
ccfkms
Clustering with Conjugate Convex Functions
circleplot.dist
Plotting Distance Graphs
order
Improving the Presentation of Matrix Objects
lmplot
Plotting Logical Matrices