Abstract

Despite the large success of Random Forests, there barely exist suitable visualizations, which allow a fast and accurate understanding of how well they perform a certain task and what leads to this performance. This work proposes an exemplar-driven visualization illustrating the most important key concepts of a Random Forest classifier, namely strength and correlation of the individual trees as well as strength of the whole forest. A visual inspection of the results enables not only an easy performance evaluation but also provides further insights why this performance was achieved and how parameters of the underlying Random Forest should be changed in order to further improve the performance.

Code

VRF - Visual Random Forests
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VRF provides a Matlab script, which visualizes the data of a given RF-classifier by three-dimensional plots. All important properties of an RF are easily comprehensible from the rendered 3D space (ie. strength of the whole forest as well as of individual trees, correlation of the trees, leaf impurity, and split dimensions).

Besides Matlab, no other external dependencies are required.

Code

Citation

If you use VRF for your research please cite:

R. Hänsch, O. Hellwich, Performance Assessment and Interpretation of Random Forests by Three-Dimensional Visualizations, IVAPP 2015 - Proceedings of the International Conference on Information Visualization Theory and Application, March 2015

@INPROCEEDING{ Haensch:2015:IVAPP15,
  author = {Hänsch, Ronny and Hellwich, Olaf},
  title  = {Performance Assessment and Interpretation of Random Forests by Three-Dimensional Visualizations},
  booktitle = {Proceedings of the International Conference on Information Visualization Theory and Application, IVAPP 2015},
  volume = {tba},
  pages  = {tba},
  year   = {2015}
}

License

VRF - Visual Random Forests Copyright (c) 2015, Ronny Hänsch

VRF is free software: you can redistribute it and/or modify it under the terms of the Modified BSD License.

VRF is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the Modified BSD License for more details.

Related

Performance Assessment and Interpretation of Random Forests by Three-Dimensional Visualizations
Hänsch, R. & Hellwich, O., , IVAPP 2015 - Proceedings of the International Conference on Information Visualization Theory and Application, Berlin, Germany, March 2015.

Please see also RFVis for a more sophisticated and very comfortable interactive tool to visualize and analyze a Random Forest.