Why is Dimensionality Reduction Important in Catalysis?
Dimensionality reduction is crucial in catalysis for several reasons:
Simplified Models: It helps in creating simplified models that are easier to understand and computationally less intensive. Noise Reduction: By eliminating less important variables, dimensionality reduction can help reduce noise in the data. Enhanced Visualization: It aids in visualizing high-dimensional data in two or three dimensions. Improved Performance: It can enhance the performance of machine learning algorithms used for predicting catalytic behavior.
