R: Kernel Distance Metric Learning for Mixed-Type Data

# Kernel Distance Metric Learning for Mixed-Type Data

## Documentation for package ‘kdml’ version 1.1.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

kdml-package | Kernel Metric Learning for Mixed-type Data
confactord | Mixed-type Data Generation with True Membership Labels
dkps | Distance using Kernel Product Similarity (DKPS) for Mixed-type Data
dkss | Distance using Kernel Summation Similarity (DKSS) for Mixed-type Data
kdml | Kernel Metric Learning for Mixed-type Data
kss | Kernel Summation Similarity Function (KSS) for Mixed-type Data
mscv.dkps | Maximum-similarity Cross-validated (MSCV) bandwidth selection method for the Distance using Kernel Product Similarities (DKPS)
mscv.dkss | Maximum-similarity Cross-validated (MSCV) bandwidth selection method for the distance using kernel summation similarity (DKSS)
spectral.clust | Spectral Clustering using Similarity or Distance Matrices