annembed 0.1.6

a Rust implementation of a dimension reduction à la Umap
Documentation 
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//! module hdbscan
//!
//! The implementation here is a Single Linkage algorithm.
//! It is a fast algorithm based on an a k-nn algorithm and minimum spanning tree.
//! The choice of the Single Linkage Algorithm is justified by the Carlsson, Memoli paper
//! cited below.
//!
//! We build upon the crates hnsw-rs for the k-nn implementation and petgraph
//! for the the minimum spanning tree (Kruskal) algorithm.
//!
//!
//! The following papers give some light on the theoretical problems underlying the hierarchical clustering algorithms:
//!
//! - Density-Based Clustering Based on Hierarchical Density Estimates.
//!   Campello Moulavi Sander (2013)
//!
//! - Characterization, Stability and Convergence of Hierarchical Clustering Methods
//!   Carlsson, Memoli. 2010
//!
//! - Consistent procedures for cluster tree estimation
//!   Chaudhuri K., DasGupta S., Kpotufe S., Von Luxburg 2014
//!
//! - Hierarchical Clustering: Objective Functions and Algorithms
//!   Cohen-Addad V., Kanade V., Mathieu C. (2017)
//!  
//!

mod kruskal;
mod sl;

// 1.  We get from the hnsw a list of edges for kruskal algorithm
// 2.  Run kruskal algorithm ,  we get a MinSpanningTree<G>
//        - iteration through the MinSpanningTree<G> gives give edges in increasing weight.
//        - construct den
// 3. Get an ordered list of edges.