Dimensionality reduction and supervised analysis enable trait linkage

Supervised and unsupervised dimensionality reduction (PCA, LDA) along with regression (e.g., LASSO) convert high-dimensional spectral data into key features and clusters, making it possible to predict and classify sample traits such as Scoville heat, ABV, and species identity.

Part of Chain