Datumbox Machine Studying Framework 0.6.1 Launched

The brand new model of Datumbox Machine Studying Framework has been launched! Obtain it now from Github or Maven Central Repository.

What’s new?

The principle focus of model 0.6.1 is to resolve varied bugs, cut back reminiscence consumption and enhance pace.

Let’s see intimately the modifications of this model:

1. Bug Fixes: A minor situation associated to Unreleased Sources has been detected and glued on the Assessments of Dataset class. Additionally a reminiscence leak was detected and patched on the AutoCloseConnector class.
2. Improved Reminiscence Footprint: The shutdown hooks are actually eliminated when shut() is known as; this improves reminiscence utilization. Additionally the TypeInference class has been up to date to scale back reminiscence consumption.
3. Velocity: The TextClassifier class has been refactored and few pace enhancements have been launched.
4. Staying Up-to-date: All dependencies and maven plugins used within the challenge have been up to date to the most recent secure variations. Few extra particulars on crucial dependencies: The framework now makes use of MapDB 1.0.8 and it’s inside my plans to maneuver to MapDB 2.0 as soon as a secure model is launched. Furthermore I created a Mavenized model of LIBSVM; we at present use essentially the most up to date model which is the three.21.

As anticipated the model 0.6.1 is backwards appropriate with the model 0.6.0 of the framework.

Subsequent steps & roadmap

The event of Datumbox Framework will proceed specializing in model 0.7.0. I plan to introduce couple of modifications on the structure of the framework and additional enhance the pace and reminiscence footprint of the library. For extra details about the roadmap take a look on the earlier launch announcement.

Don’t neglect to obtain the code of Datumbox v0.6.1 from Github. The library is accessible additionally on Maven Central Repository.

I’m trying ahead to your feedback and proposals. Pull requests are all the time welcome! 🙂