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 Aliases
- Simplified
Result
usingHierarchicalError
as error type