PyXAI also includes algorithms for correcting tree-based models when their predictions conflict with pieces of user knowledge. This more tricky facet of XAI is seldom offered by existing XAI systems.

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“Rather than trying to create models that are inherently interpretable, there has been a recent explosion of work on ‘explainable ML’, where a second (post hoc) model is created to explain ...

ELI5, short for “Explain Like I’m 5,” is a Python library designed for visualizing ... while others might work best with decision tree models. Moreover, some models are inherently more explainable ...

While Markov Chain Monte Carlo methods are typically used to construct Bayesian Decision Trees, here we provide a deterministic Bayesian Decision Tree algorithm that ... for a technique that provides ...

Abstract: Tree-based models have been successfully applied to a wide variety of tasks, including time series forecasting. They are increasingly in demand and widely accepted because of their ...