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.
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.
Stars
166
Forks
66
Language
Java
License
Apache-2.0
Category
Last pushed
Oct 29, 2020
Commits (30d)
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