How Do Random Forests Handle High-Dimensional Data in Nanotechnology?
Random forests are effective in managing high-dimensional data, which is common in nanotechnology research. Each tree in the forest is built using a random subset of features, which helps in reducing the dimensionality and focusing on the most relevant variables. This process not only improves prediction accuracy but also aids in identifying key features that influence the properties and behaviors of nanostructures.
