What are the Challenges of Using Random Forests in Toxicology?
Despite their advantages, random forests come with some challenges:
Interpretability: The models can be complicated to interpret, which is a critical aspect in toxicology for regulatory purposes. Computational Resources: Training large random forests can be computationally intensive. Data Requirements: Large and diverse datasets are often required to build robust models, which may not always be available.
