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Project Description

mltool is a simple Learning to Rank tool to build a regression tree based ranking model. Currently mltool supports simple CART and Random Forest. The implementation is strongly inspired by rt-rank, but it lacks the support of Gradient Boosting Regression Trees.

Overview

Features

Despite rt-rank, mltool provides:

  • A parameter to set the seed for the random number generator to make the training deterministic
  • Serializable model
  • Show feature information gain statistics at the end of the training
  • Can be used as an API

Some highlights compared to other Random Forest implemented for Python:

  • The implementation of the Random Forest makes use of numpy and it is quite optimized
  • Parallel Random Forest training

Installation

Install from PyPI using pip:

$ pip install mltool

Now you can run mltool:

$ mltool -h

Documentation

The documentation is hosted by Read the Docs at the following url: http://readthedocs.org/docs/mltool/en/latest/

Future

  • add support for Stochastic Gradient Boosting Regression Trees
  • add support for simple regression and/or classification (i.e. not just focus on ranking)
Release History

Release History

0.6

This version

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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0.5.1b

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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Download Files

Download Files

TODO: Brief introduction on what you do with files - including link to relevant help section.

File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
mltool-0.6.tar.gz (9.8 kB) Copy SHA256 Checksum SHA256 Source Apr 9, 2012

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