tgsmith61591/clust4j

A suite of classification clustering algorithm implementations for Java. A number of partitional, hierarchical and density-based algorithms including DBSCAN, k-Means, k-Medoids, MeanShift, Affinity Propagation, HDBSCAN and more.

49
/ 100
Emerging

This project offers a collection of tools to help you automatically group your data based on similarities. You input a spreadsheet or dataset, and it sorts your entries into distinct categories or identifies close relationships, without you needing to tell it what those categories are beforehand. It's designed for data scientists, analysts, or researchers who need to discover patterns and segment information within their datasets.

166 stars. No commits in the last 6 months.

Use this if you need to find inherent groupings within your data, such as identifying customer segments, classifying biological samples, or detecting anomalies, and you prefer to work within a Java environment.

Not ideal if you need a solution for production environments or if you are not comfortable working with Java code.

data-segmentation pattern-recognition customer-profiling biological-classification anomaly-detection
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 23 / 25

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Stars

166

Forks

66

Language

Java

License

Apache-2.0

Last pushed

Oct 29, 2020

Commits (30d)

0

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