Dataset and source code used in the paper:

Fabio Fabris, Aoife Doherty, Daniel Palmer, Joao Pedro de Magalhaes and Alex A. Freitas. A new approach for interpreting random forest models and its application to the biology of ageing. To appear in Bioinformatics journal."

Link to the paper.

Date: 30th of January, 2018.


Here we make publicly available the source code and datasets used in the paper "A new approach for interpreting random forest models and its application to the biology of ageing". We also present information about the instances and features both in standard web format and XML format.

General information about the data - Dataset creation procedure and dataset statistics. Please refer to the paper for more details.

Description of the Features - Feature identifiers, feature names and links to an external database.

Description of the Instances - Instance (gene) identifiers, instance names, instance descriptions and links to an external database. The i-th instance in the arff file corresponds to the i-th instance in this page.

Original dataset - The original dataset used in the paper in the arff format (used by the data mining tool WEKA). Click here for more details about the arff format.

Original source code - The original source code used in the paper. Please refer to the "readme.txt" file in the zip file for more details about the implementation and the contents of the arff file.