Principal Component Analysis

A PCA is a statistical technique used for dimensionality reduction in data analysis and machine learning. The iris dataset is a classic dataset used in statistics, machine learning, and data visualization. The dataset consists of 150 samples from three species of flowers (Iris virginica, Iris setosa, and Iris versicolor). For each sample, the following features were measured: length and width of the sepal and petals in centimeters. Need more information? Check out the community guide: https://community.julius.ai/t/guide-introduction-to-principal-component-analysis-in-r/3509