kanyun-inc / ytk-learn

Ytk-learn is a distributed machine learning library which implements most of popular machine learning algorithms(GBDT, GBRT, Mixture Logistic Regression, Gradient Boosting Soft Tree, Factorization Machines, Field-aware Factorization Machines, Logistic Regression, Softmax).

Date Created 2017-05-17 (7 years ago)

Commits 102 (last one 5 years ago)

Stargazers 347 (0 this week)

Watchers 36 (0 this week)

Forks 76

License mit

Ranking

RepositoryStats indexes 584,353 repositories, of these kanyun-inc/ytk-learn is ranked #119,053 (80th percentile) for total stargazers, and #59,963 for total watchers. Github reports the primary language for this repository as Java, for repositories using this language it is ranked #7,356/28,264.

kanyun-inc/ytk-learn is also tagged with popular topics, for these it's ranked: machine-learning (#2,495/7926), spark (#178/536), distributed (#170/378), hadoop (#60/180)

Other Information

kanyun-inc/ytk-learn has 4 open pull requests on Github, 0 pull requests have been merged over the lifetime of the repository.

There have been 4 releases, the latest one was published on 2018-05-10 (6 years ago) with the name version 0.0.4.

All Topics

gbm gbdt spark hadoop distributed machine-learning logistic-regression factorization-machines

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The primary language is Java but there's also others...

updated: 2024-11-20 @ 11:54am, id: 91575491 / R_kgDOBXVUww