Covers feature extraction, clustering, and classification methods for high-dimensional datasets and behavioral analysis using PCA, t-SNE, k-means, GMM, and various classification algorithms.
Explores the nearest neighbor classifier method, discussing its limitations in high-dimensional spaces and the importance of spatial correlation for effective predictions.