How Can Machine Learning Aid in Handling High Dimensional Datasets?
Machine learning (ML) offers powerful tools to tackle the challenges posed by high dimensional datasets:
Dimensionality Reduction: Techniques such as Principal Component Analysis (PCA) and t-SNE help reduce the number of variables while preserving essential information, making the data more manageable. Pattern Recognition: ML algorithms can identify patterns and correlations within the data that may not be apparent through conventional analysis methods. Predictive Modeling: Supervised learning techniques, including regression and classification, can develop models that predict catalyst performance based on input features.
