High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
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README.md

Hex.pm Project Status Travis

What is xLearn?

xLearn is a high performance, easy-to-use, and scalable machine learning package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM), which can be used to solve large-scale machine learning problems. xLearn is especially useful for solving machine learning problems on large-scale sparse data, which is very common in Internet services such as online advertisement and recommender systems in recent years. If you are the user of liblinear, libfm, and libffm, now xLearn is your another better choice.

Get Started! (English)

Get Started! (中文)

Performance

xLearn is developed by high-performance C++ code with careful design and optimizations. Our system is designed to maximize CPU and memory utilization, provide cache-aware computation, and support lock-free learning. By combining these insights, xLearn is 5x-13x faster compared to similar systems.

Ease-of-use

xLearn does not rely on any troublesome third-party library, and hence users can just clone the code and compile it by using cmake. Also, xLearn supports very simple Python and CLI interface for data scientists, and it also offers many useful features that have been widely used in machine learning and data mining competitions, such as cross-validation, early-stop, etc.

Scalability

xLearn can be used for solving large-scale machine learning problems. First, xLearn supports out-of-core training, which can handle very large data (TB) by just leveraging the disk of a PC. In addition, xLearn supports distributed training, which scales beyond billions of example across many machines by using the Parameter Server framework.

What's New

  • 10/14/2018 xLearn 0.3.3 version release. Main update:

    • Fix segmentation fault in prediction task.
    • Update early-stop meachnism.
  • 09/21/2018 xLearn 0.3.2 version release. Main update:

    • Fix bugs in previous version
    • New TXT format for model output
  • 08/09/2018 xLearn uses the new logo:

  • 07/09/2018 The Chinese document is available now!

  • 08/03/2018 xLearn 0.3.0 version release. Main update:

    • Fix bugs in previous version
    • Solved the memory leak problem for on-disk learning
    • Support TXT model checkpoint
    • Support Scikit-Learn API
  • 18/12/2017 xLearn 0.2.0 version release. Main update:

    • Fix bugs in previous version
    • Support pip installation
    • New Documents
    • Faster FTRL algorithm
  • 11/24/2017 The first version (0.1.0) of xLearn release !