Crate linfa_hierarchical
source · [−]Expand description
Hierarchical Clustering
linfa-hierarchical provides an implementation of agglomerative hierarchical clustering.
In this clustering algorithm, each point is first considered as a separate cluster. During each
step, two points are merged into new clusters, until a stopping criterion is reached. The distance
between the points is computed as the negative-log transform of the similarity kernel.
Documentation: latest.
The big picture
linfa-hierarchical is a crate in the linfa ecosystem,
a wider effort to bootstrap a toolkit for classical Machine Learning implemented in pure Rust,
akin in spirit to Python’s scikit-learn.
Current state
linfa-hierarchical implements agglomerative hierarchical clustering with support of the
kodama crate.
Structs
Agglomerative hierarchical clustering
Checked version of HierarchicalCluster
Enums
Criterion when to stop merging
Error variants from parameter construction
A method for computing the dissimilarities between clusters.
Type Definitions
Simplified Result using HierarchicalError as error type