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§
- Hierarchical
Cluster - Agglomerative hierarchical clustering
- Valid
Hierarchical Cluster - Checked version of
HierarchicalCluster
Enums§
- Criterion
- Criterion when to stop merging
- Hierarchical
Error - Error variants from parameter construction
- Method
- A method for computing the dissimilarities between clusters.
Type Aliases§
- Result
- Simplified
ResultusingHierarchicalErroras error type