PCA helps to assess which original samples are similar and different from each other. Most of the variation, which is easy to visualize and summarise the feature of original high-dimensional datasets in New set of uncorrelated variables called principal component (PC) while retaining the most possible variation. Method that used to interpret the variation in high-dimensional interrelated dataset (dataset with a large number of variables)
PCA is a classical multivariate (unsupervised machine learning) non-parametric dimensionality reduction.Eigendecomposition of the covariance matrix What is Principal component analysis (PCA)?.Principal component analysis (PCA) with a target variable.What is Principal component analysis (PCA)?.
Principal component analysis (PCA) and visualization using Python (Detailed guide with example)
