What Are Some Common Challenges in Using RapidMiner for Catalysis and How Can They Be Overcome?
Despite its advantages, there are some challenges associated with using RapidMiner in catalysis research:
Data Quality: Poor quality data can lead to inaccurate models. Ensuring high-quality data through rigorous preprocessing is essential. Model Interpretability: Complex models can be difficult to interpret. Using simpler models or techniques like feature importance can help. Computational Resources: Large datasets require significant computational resources. Leveraging distributed computing can mitigate this issue.
