Abstract: As an efficient feature engineering tool, principal component analysis (PCA) has been widely used for feature extraction in the past decades. While a deep form of PCA has been developed for ...
This standalone MATLAB project generates edge groups from images, converts manual polyline annotations into edge-group labels, and trains RF and PCA/SVM classifiers. The repository includes the ...
Abstract: Sparse principal component analysis (SPCA) is widely used for dimensionality reduction and feature extraction in high-dimensional data analysis. Despite many methodological and theoretical ...
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