# oracle/tribuo

Tribuo - A Java machine learning library

Repository: https://github.com/oracle/tribuo
Canonical: https://ross.abutalabs.com/products/tribuo
Homepage: https://tribuo.org
Language: Java
License: Apache-2.0
License Family: permissive
Topics: machine-learning, java, deep-learning, classification, regression, clustering, nlp, ml
Last push: 2026-05-07T19:27:41+00:00

## Health v2 (maintenance only)
Score: 59/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 81, release rhythm 8, longevity 100
- inputs: {"age_days": 2269, "days_push": 118, "days_rel": 516, "gap_med": null, "n_releases_24m": 1}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1417, forks 197 (observed 2026-08-28T04:04:40.087835+00:00)

## What it is
Tribuo is a Java machine learning library from Oracle Labs providing classification, regression, clustering, anomaly detection, and multi-label prediction with a strongly typed, unified API. It wraps libraries like XGBoost and TensorFlow, supports ONNX import/export, and records provenance for models, datasets, and evaluations.

## Use cases
- train a classification model in Java
- run scikit-learn or pytorch models in a JVM app via ONNX
- do regression and clustering on the JVM
- track model provenance for reproducible ML experiments
- build a text classification pipeline in Java
- export Java-trained models to ONNX for cloud deployment

## When to choose
- you need ML in a pure Java/JVM codebase without Python
- you want strongly typed models and built-in provenance tracking
- you need to deploy Python-trained models inside Java services via ONNX

## When to avoid
- your workflow is Python-centric with pandas and scikit-learn
- you need cutting-edge deep learning research features
- you need GPU-heavy training at scale

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, nlp, deep-learning, serialization, data-science
- domain: machine-learning, data-science, developer-tools
- platform: jvm, cross-platform, windows
- tags: classification, regression, clustering, anomaly-detection, multi-label, onnx, provenance, xgboost, tensorflow, oracle, natural-language-processing, linux, macos

## Member repositories
- oracle/tribuo (main) score 59

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:40.087835+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:38:02.111191+00:00, confidence not recorded.
  - readme: https://github.com/oracle/tribuo (fetched 2026-08-28T04:04:40.087835+00:00, sha 11ad44ca082a)
  - homepage: https://tribuo.org (fetched 2026-08-29T11:50:40.457904+00:00, sha ef52af58d6fe)
  - site_page: https://tribuo.org/learn/4.3/docs (fetched 2026-08-29T11:50:40.460323+00:00, sha 2fca30865e65)
  - site_page: https://tribuo.org/learn/4.3/docs/features.html (fetched 2026-08-29T11:50:40.462354+00:00, sha 0e52e465cff2)
  - site_page: https://tribuo.org/learn/4.3/faq.html (fetched 2026-08-29T11:50:40.464180+00:00, sha 0afb6193c9b0)
- Data as of 2026-08-30T08:39:29.467469+00:00.