Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Ytk Learn | 351 | 2 years ago | n,ull | mit | Java | |||||
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). | ||||||||||
Spark Fm Parallelsgd | 212 | 8 years ago | 3 | apache-2.0 | Jupyter Notebook | |||||
Implementation of Factorization Machines on Spark using parallel stochastic gradient descent (python and scala) | ||||||||||
Spark Fm | 51 | 4 years ago | 3 | apache-2.0 | Scala | |||||
A parallel implementation of factorization machines based on Spark | ||||||||||
Algorithmsonspark | 27 | 6 years ago | Scala | |||||||
Some popular algorithms(dbscan,knn,fm etc.) on spark | ||||||||||
Glint Fm | 25 | 7 years ago | 1 | apache-2.0 | Scala | |||||
Factorization Machines on Spark and Glint | ||||||||||
Multinomial Factorization Machines | 20 | 8 years ago | apache-2.0 | Terra | ||||||
Multinomial Factorization Machines | ||||||||||
Advanced Factorization Of Machine Systems | 16 | 7 years ago | apache-2.0 | Jupyter Notebook | ||||||
GSOC 2017 - Apache Organization - # Implementation of Factorization Machines on Spark using parallel stochastic gradient descent (python and scala) | ||||||||||
Customer_churn_prediction | 12 | 4 years ago | Python | |||||||
零售电商客户流失模型,基于tensorflow,xgboost4j-spark,spark-ml实现LR,FM,GBDT,RF,进行模型效果对比,离线/在线部署方式总结 |