PLT Documentation

Preference learning (PL) is a core area of machine learning that handles datasets with ordinal relations. As the number of generated data of ordinal nature such as ranks and subjective ratings is increasing, the importance and role of the PL field becomes central within machine learning research and practice.

The Preference Learning Toolbox (PLT) is an open source software application and package which supports the key data modelling phases incorporating various popular data pre-processing, feature selection and preference learning methods.

PLT Features:

• Dataset Pre-processing (including automatic feature extraction)
• Automatic Feature Selection (SFS)
• Preference Learning Algorithms (RankSVM, ANN-Backpropagation, RankNet)
• Experiment Reporting and Model Storage

Contents:

The documentation for PLT consists of the following:

• API Reference

• Tutorial: How To Set Up And Run An Experiment
• Tutorial: How To Add An Algorithm Or Method

Indices and tables

• Index
• Module Index
• Search Page