Conclusive Local Interpretation Rules for Random Forests through LionForests
LionForests v2, extends our previous component LionForests, and it is a random forest-specific interpretation technique, which provides rules as explanations. It is applicable from binary classification tasks to multi-class classification and regression tasks, and it is supported by a stable theoretical background.
Install & Run: Please ensure you have docker installed on your desktop. Download the component and then navigate to the subfolder through your terminal. Afterwards:
>>> docker build -t lionforests .
(The dot is necessary)
After succesfully installing LionForests, please do:
>>> docker run -p 8888:8888 lionforests
Then, in your terminal copy the localhost url and open it in your browser.
Additional information: Experimentation, including sensitivity analysis and comparison with state-of-the-art techniques, is also performed to demonstrate the efficacy of our contribution. In the scientific report, we highlight a property of LionForest that distinguishes it from other techniques that do not have this property.
Two Acumos components based on this asset are available in the AI4EU Experiments marketplace: LionForests on Adult Classification, and LionForests GUI (generic component).