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).
This is a distributed machine learning library that helps data scientists and machine learning engineers develop and deploy predictive models. It takes your datasets as input and outputs trained models that can make predictions. It's designed for practitioners who need to build and run machine learning algorithms on single machines or across large-scale distributed environments like Hadoop or Spark.
350 stars. No commits in the last 6 months.
Use this if you are a data scientist or ML engineer building predictive models and need a robust, distributed framework for common machine learning algorithms.
Not ideal if you are looking for a simple, non-distributed tool for quick model prototyping or if you prefer programming languages other than Java.
Stars
350
Forks
76
Language
Java
License
MIT
Category
Last pushed
Jul 06, 2022
Commits (30d)
0
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