Dimension reduction properties and supervised learning ofcomplex Functional Data

Key Points

• Enhanced dimension reduction techniques improve the accuracy of supervised learning models.
• The study demonstrates that optimized functional data representation leads to better predictive performance.
• Assessment of machine learning approaches shows significant improvements in handling complex data structures.
• This work supports the need for advanced analysis techniques in dealing with high-dimensional functional data.