h2oai/h2o-2
Please visit https://github.com/h2oai/h2o-3 for latest H2O observed · 2026-08-28
Health v2 · maintenance only
10/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases archived
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 4956
- days_rel: n/a
- days_push: 678
- n_releases_24m: 0
Adoption not part of the score
2249 stars · 547 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
H2O-2 is a Java-based distributed machine learning and math engine that scales statistics and predictive modeling over Big Data platforms like Hadoop. It offers algorithms such as Random Forest, GLM, logistic regression, and k-Means accessible via R, REST, and JSON APIs, and has been superseded by H2O-3.
Use cases
- run machine learning models on hadoop big data
- train random forest and glm models at scale
- do predictive modeling from R or REST API
- explore large datasets with an R-like parser
- score models online in real time
- distributed k-means clustering on big datasets
When to choose
- maintaining an existing H2O-2 deployment
- you specifically need the legacy H2O-2 algorithms or interfaces
When to avoid
- starting a new machine learning project
- you want the actively developed H2O platform
- you need modern algorithms like deep learning or AutoML
Facets
application · maturity maintenance
machine-learning data-science http-server machine-learning data-science big-data analytics jvm windows cross-platform hadoop bigdata glm random-forest k-means r-integration rest-api legacy superseded-by-h2o-3 linux macos
1 source
- readme: https://github.com/h2oai/h2o-2 · fetched 2026-08-28 · 0a3fabe28ee6
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| h2oai/h2o-2 | main | 10 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem