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).

distributed

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350 Stars

76 Forks

350 Watchers

Java Language

mit License

100 SrcLog Score

Cost to Build

$50.9K

Market Value

$110.5K

How is this calculated?

Growth over time

9 data points · 2021-07-01 → 2026-04-01

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What is the kanyun-inc/ytk-learn GitHub project? Description: "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).". Written in Java. Explain what it does, its main use cases, key features, and who would benefit from using it.

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git clone https://github.com/kanyun-inc/ytk-learn.git

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[email protected]:kanyun-inc/ytk-learn.git

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Download master.zip

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