Tag: Noise Reduction in Data

Introduction: What is PCA? Principal Component Analysis (PCA) is a powerful unsupervised machine learning technique used for dimensionality reduction. It transforms high-dimensional data into a lower-dimensional space while retaining as much variability as possible. By simplifying datasets, PCA helps improve model performance, reduce computational cost, and make data visualization easier. How Does PCA Work? Applications… Read more