Preprocess the data by normalizing pixel values and standardizing the dataset. Train a Random Forest Classifier on the original high-dimensional data. Apply PCA to reduce the dimensionality of the ...

we propose a method that combines graph-regularized principal component analysis (graph-regularized PCA) and an ensemble learning framework, random forest, to capture effective low-dimensional ...

# ### Python's pathlib module provides a modern and Pythonic way of working with file paths, making code more readable and maintainable. With pathlib , you can represent file paths with dedicated Path ...

This architecture attempts to improve Random Forest's ability to recognize feature interdependencies. A performance improvement is achieved by creating a PCA model within each tree. This PCA model ...