Principal component analysis (PCA) is a classical machine learning technique. The goal of PCA is to transform a dataset into one with fewer columns. This is called dimensionality reduction. The ...

Principal Component Analysis from Scratch Using Singular Value Decomposition with C# Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a classical ML technique ...

Protein candidates enriched in PCa vs BPH were further evaluated in-silico using a custom-made pipeline. For this purpose, seven publicly available transcriptomic PCa datasets (ntotal = 875) were ...