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