: In health management models, use data downscaling to focus on high-risk prediction analysis. Semantic Priors : If data is scarce (
For complex variables, such as those representing continuous data in polymer chemistry or health monitoring, you must define the design space: mai.qiuyi.1.var
Once data is collected, apply these techniques to handle high-dimensional variable sets: : In health management models, use data downscaling
: Divide the variable into specific intervals that span the desired range. A common threshold is to stop splitting branches
: Factors kept the same throughout the experiment to ensure meaningful results. 2. Discretization and Restrictions
: Confirm the variable aligns with the overall research question and documented intermediate steps.
: Use methods like PChclust (Principal Component Hierarchical Clustering) to summarize variance. A common threshold is to stop splitting branches if the first principal component explains more than 70% of the variance.