Mullpy is a machine-learning library that mainly aim to solve multi-label problems. It is classifier independent, has many ensemble capabilities (diversity methods like bagging, random subspaces, etc.) and automated results presentation (Excel, images as ROC or class-separated info, etc.). It is fully configurable. At the moment supports Neural Networks and classifiers defined in files. It is working on python3.3.

Features

  • Learning
  • Testing
  • Validation
  • Classifier independent
  • Auto-configuring some learning parameters
  • Automatic display of completely classifier info in excel format
  • Automatic display of figures (ROCs, scatters, easy to implement new ones)
  • Diversity measures for the ensembles in excel table
  • Meta-Ensembles construction (real outputs, oracle outputs)
  • SMV/WMV/ easy to implement new ones
  • Modular code that permits quick expansion

Project Activity

See All Activity >

License

GNU General Public License version 3.0 (GPLv3)

Follow mullpy

mullpy Web Site

Other Useful Business Software
Paessler: Easy to Use With Enterprise Power. Free Trial Icon
Paessler: Easy to Use With Enterprise Power. Free Trial

A low-code dashboard makes monitoring intuitive for any admin, while scripting and custom sensors give experts full control.

You shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
Get Free Download
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of mullpy!

Additional Project Details

Languages

English

Intended Audience

Information Technology, Quality Engineers, Science/Research

Programming Language

Python

Related Categories

Python Bio-Informatics Software, Python Machine Learning Software

Registered

2013-03-10