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scikit-learn compatibel multi-label classification

Home Page: http://skml.readthedocs.io/en/latest/

License: MIT License

Makefile 0.70% Python 99.30%
machinelearning multi-label-classification scikit-learn machine-learning machine-learning-library multi-label-learning multi-label-problem python python3 artificial-intelligence data-science data-mining multi-label

skml's Introduction

skml

https://travis-ci.org/ChristianSch/skml.svg?branch=master

scikit-learn compatible multi-label classification implementations.

A multi-class classification (MLC) problem is given, if a subset of labels (picture of equation) shall be predicted for an example.

Currently Supported

  • Problem Transformations:
    • Binary Relevance
    • Label Powerset
    • Classifier Chains
    • Probabilistic Classifier Chains
  • Ensembles:
    • Ensemble Classifier Chain

Installation

For production install via pip: ` pip install skml `

For development, clone this repo, change to the directory of skml and inside of the skml directory run the following: ` pip install -e .[dev] python setup. `

Python Supported

Due to dependencies we do not check for a working distribution of skml for the following Python versions:

  • 3.2

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