Clustering for Business Analytics
Clustering a Sparse Symmetric Distance Matrix
Clustering with Conjugate Convex Functions
Plotting Distance Graphs
Plotting Logical Matrices
Dummy Coding
Converting Ordered Factors
Extract from a Proximus Object
Generalized k-Nearest Neighbor Classification
Matrix Image Plots
Interpolating Logical Matrices
Plotting Logical Matrices
Hierarchical Greedy Ordering
Conciseness of Presentation Measures
Optimal Leaf Ordering of Binary Trees.
Improving the Presentation of Matrix Objects
Plotting Edit Transcripts and Sequence Alignments
Clustering with Conjugate Convex Functions.
Rock Clustering
Proximus
Block Uniform Logical Matrix Deviates
Rock Clustering
Align Sequences to a Center
Centroid Sequences
Sequence Distance Computation
Edit Transcripts and Sequence Alignments
Conciseness of Presentation Measures
Summarizing Proximus Objects
Implements clustering techniques such as Proximus and Rock, utility functions for efficient computation of cross distances and data manipulation.