Maximising contrast when exploring high dimensionality data: Supervised Principal Components

Principal Components Analysis (PCA) and its sibling Singular Value Decomposition (SVD) are commonly-used dimensionality reduction tools that can dramatically improve the performance of supervised and unsupervised Machine Learning algorithms. They are also very useful in exploratory data analysis to expose…....

By Vanita Pandey